Data Security

Data erasure is a software-based process that involves data sanitization or in plain words ‘data wiping’ so that no traces of data remain recoverable. This helps with the prevention of data leakage and the protection of sensitive information like trade secrets, intellectual property, or customer information.  

By 2025, it is estimated that data will grow up to 175 Zettabytes, and with great data comes great responsibility. Data plays a pivotal role in both personal and professional lives. May it be confidential records or family photos, data security is important and must be always endorsed.   

As the volume of digital information continues to grow, so does the need for safeguarding and securing data. Key data breach statistics show that 21% of all folders in a typical company are open to everyone leading to malicious attacks indicating a rise in data leakage and 51% criminal incidents.

 

 

Understanding data erasure 

Data erasure is a fundamental practice in the field of data security and privacy. It involves the permanent destruction of data from storage devices like hard disks, solid-state devices, or any other digital media through software or other means.  

 

 

This practice ensures that data remains completely unrecoverable through any data recovery methods while the device remains reusable (in case software is being used). Data erasure works in regard to an individual person who is disposing of a personal device as well as organizations handling sensitive business information. It guarantees responsible technology disposal.  

 

The science behind data erasure 

Data erasure is also known as ‘overwriting’, it involves a process of writing on data with a series of 0s and 1s making it unreadable and undiscoverable. The overwriting process varies in the number of passes and patterns used. The type of overwriting depends on multiple factors like the nature of the storage device, the type of data at hand, and the level of security that is needed.  

 

The ‘number of passes’ refers to the number of times the overwriting process is repeated for a certain storage device. Each pass essentially overwrites the old data with new data. The greater the number of passes, the more thorough the data erasure process is making it increasingly difficult to recover the demolished data.  

‘Patterns’ can make data recovery extremely challenging. This is the reason why different sequences and patterns are written to the data during each pass. In essence, the data erasure process can be customized to cater to different types of scenarios depending upon the sensitivity of the data being erased. Moreover, data erasure is also used to verify whether the erasure process was successful.  

Read more -> Master data security in warehousing 

The need for data erasure 

Confidentiality of business data, prevention of data leakage, and regulation with compliance are some of the reasons we need methods like data erasure especially when someone is relocating, repurposing, or putting a device to rest. Traditional methods like data deletion make the data unavailable to the user but provide the privilege of recovering it through different software.

Likewise, the destruction of physical devices renders the device completely useless. For this purpose, a software-based erasure method is required. Some crucial factors that drive the need are listed below:  

 

Protection of sensitive information:  

Protecting sensitive information from unauthorized access is one of the primary reasons for having data erasure. Data branches or leakage of confidential information like customer information, trade secrets, or proprietary information can lead to severe consequences.  

Thus, when the amount of data begins to get unmanageable and enterprises look forward to disposing of a portion of it, it is always advisable to destroy the data in a way that it is not recoverable for misuse later. Proper data erasure techniques help to mitigate the risk associated with cybercrimes.  

 

Read more -> Data privacy and data anonymization techniques 

 

Data lifecycle management:  

The data lifecycle management process includes secure storage and retrieval of data but alongside operational functionality, it is also necessary to dispose of the data properly. Data erasure is a crucial aspect of data lifecycle management and helps to responsibly remove data when it is no longer needed.  

 

Compliance with data protection regulations:  

Data protection regulations in different countries require organizations to safeguard the privacy and security of an individual’s personal data. To avoid any legal consequences and potential damages from data theft, breach, or leakage, data erasure is a legal requirement to ensure compliance with the imposed regulations.  

 

Examples of data erasure: 

 

Corporate IT asset disposal: 

When a company decides to retire its previous systems and upgrade to new hardware, it must ensure that any old data that belongs to the company is securely erased from the older devices before they can be sold, donated or recycled.

This prevents sensitive corporate information from falling into the wrong hands. The IT department can use certified data erasure software to securely wipe all sensitive company data, including financial reports, customer databases, and employee records, ensuring that none of this information can be recovered from the devices. 

 

Healthcare data privacy: 

Like the corporate industry, Healthcare organisations tend to store confidential patient information in their systems. If the need arises to upgrade these systems, they must ensure secure data erasure to protect patient confidentiality and to comply with healthcare data privacy regulations like HIPAA in the United States. 

 

Cloud services:  

Cloud service providers often have data erasure procedures in place to securely erase customer data from their servers when requested by customers or when the service is terminated. 

 

Data center operations:  

Data centres often have strict data erasure protocols in place to securely wipe data from hard drives, SSDs, and other storage devices when they are no longer in use. This ensures that customer data is not accessible after the equipment is decommissioned. 

 

Financial services:  

In a situation where a stock brokerage firm needs to retire its older trading servers. These servers would indefinitely contain some form of sensitive financial transaction data and customer account information.

Prior to selling the servers, the firm would have to use hardware-based data erasure solutions to completely overwrite the data and render it irretrievable, ensuring client confidentiality and regulatory compliance. 

Safeguard your business data today!

In the era where data is referred to as the ‘new oil’, safeguarding it has become paramount. Many times, individuals feel hesitant to dispose of their personal devices due to the possible misuse of data present in them.  

The same applies to large organizations, when proper utilization of data has been done, standard measures should be taken to discard the data so that it does not result in unnecessary consequences. To ensure privacy and maintain integrity, data erasure was brought into practice. In an age where data is king, data erasure is the guardian of the digital realm. 

Maintaining the security and governance of data in a data warehousing is of utmost importance. As organizations increasingly rely on data warehousing for centralizing and analyzing their data, robust data security and governance practices are essential.  

In this blog post, we will cover the technical aspects of data security and governance within data warehousing, focusing on key strategies and a step-by-step approach to ensure a secure data warehouse. 

Data Security: A multi-layered approach 

In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information. This multi-layered approach is akin to constructing a fortress, where multiple lines of defense work collaboratively to safeguard your digital assets from potential threats. 

1. Perimeter Security: The First Line of Defense

Perimeter security forms the initial line of defense for your data warehouse. Firewalls stand sentinel, filtering incoming and outgoing data traffic. Intrusion detection systems (IDS) are on constant watch, promptly alerting administrators to suspicious activities that could breach the outer defenses. Just like you wouldn’t allow unauthenticated individuals through a castle gate, perimeter security ensures that unauthorized access attempts fail before reaching the core data. 

2. Encryption: Securing data in transit and at rest

Encryption serves as the digital lock and key, protecting data during transmission and at rest. Secure Sockets Layer (SSL) or Transport Layer Security (TLS) protocols encrypt data during system communication. Any interceptors attempting to eavesdrop on the communication will only encounter scrambled data. For data at rest within the castle, Advanced Encryption Standard (AES) algorithms ensure that even if unauthorized access occurs, the data remains indecipherable. 

3. Access Control: Limiting entry to authorized individuals

Just like how you can control who can enter different castle areas, access control is pivotal in data warehousing. Role-Based Access Control (RBAC) functions as the digital gatekeeper, permitting access to authorized personnel based on their organizational roles and responsibilities. Only those with legitimate reasons to access specific data can do so. Like different chambers within a castle have varying restricted access levels, RBAC enforces controlled access to data at different granularity levels. 

4. Authentication and authorization: Verifying and granting access

Authentication and authorization provide the digital equivalent of verifying someone’s identity and permitting them to enter. Multi-factor authentication adds a supplementary layer of assurance by requiring multiple forms of verification before granting access. Once authenticated, authorization ensures that the individual is allowed access only to the areas they are authorized to enter.  

Data Governance: Setting the rules 

Data governance takes on the role of a regulatory framework, guiding the responsible management, utilization, and protection of your organization’s most valuable asset—data. Just as a castle’s rules and regulations maintain order and ensure its longevity, data governance establishes the guidelines that dictate how data is acquired, stored, manipulated, and shared.  

Defining data ownership: Assigning custodianship 

Like a castle with appointed caretakers, data governance designates data owners responsible for different datasets. Data ownership extends beyond mere possession—it involves accountability for data quality, accuracy, and appropriate use. Clear data ownership ensures that data is adequately maintained, validated, and validated throughout its lifecycle. 

Data retention policies: Time-stamped preservation 

Data governance mandates the creation and adherence to data retention policies. These policies stipulate how long businesses retain different data types before being securely archived or disposed of. Like the archives house that stores historical records, data warehousing holds digital archives with valuable insights for future analysis. 

Regulatory compliance: Adhering to laws and regulations 

Data governance is a legal compass, ensuring your data practices align with industry regulations and legal requirements. Governance policies enforce adherence to GDPR, HIPAA, or SOX regulations. By establishing protection measures and privacy protocols, data governance minimizes non-compliance risk, safeguarding your organization’s reputation and the data subjects’ rights. 

Data quality and standardization: Ensuring consistency 

Data governance establishes data quality standards. This includes defining data formats, naming conventions, and validation rules. Data governance enhances data reliability by maintaining data consistency and accuracy and ensuring that analyses and decisions are based on trustworthy information. 

Data lifecycle management: Guiding data flow 

Data has a lifecycle, from its creation to its eventual archiving or deletion. Data governance maps out this journey, guiding data flow and transformation processes. It outlines how data is captured, transformed, and utilized. This organized approach enhances data visibility and simplifies data lineage tracking. 

Monitoring and auditing: Continuous oversight 

Monitoring and auditing assume the roles of vigilant sentinels, maintaining constant watch over the fortress of your data ecosystem. Just as guards patrol castle walls to prevent breaches, monitoring tools, and auditing processes ensure your data warehouse’s ongoing security, performance, and compliance. This continuous oversight is essential to detect anomalies, prevent unauthorized access, and uphold the integrity of your organization’s data. 

Real-time surveillance 

Imagine guards stationed along a castle’s walls, watching for any signs of intrusion. Similarly, monitoring tools actively observe the activities within your data warehouse. Real-time surveillance ensures that potential security threats are detected and addressed promptly, minimizing the risk of data breaches. 

Performance optimization 

Monitoring tools highlight performance bottlenecks within your data warehouse. By tracking query execution times, system resource utilization, and data load speeds, these tools reveal areas where optimization is required. This proactive approach helps maintain optimal system performance, ensuring users execute analytical queries efficiently and deliver insights without delay. 

Compliance enforcement 

Similar to guards ensuring that castle inhabitants adhere to rules, auditing enforces compliance within data warehousing. Regular audits review user activities, data access logs, and configuration changes. These audits ensure that data usage aligns with established policies and industry regulations. If any violations are detected, the auditing process generates reports that assist in corrective actions and demonstrate compliance efforts. 

Forensic analysis 

Just as guards investigate disturbances within the castle, auditing supports incident investigation within data warehousing. In case of security breaches or data anomalies, auditing logs provide a trail of events that led to the incident. This forensic analysis assists in understanding the root cause, identifying compromised data, and formulating strategies to prevent similar incidents in the future. 

Ensuring security for data warehousing

Here’s how enterprises can establish robust data security measures for their data warehouses: 

1. Comprehensive Access Control Implementation: Implement robust access controls using Role-Based Access Control (RBAC) principles. Define roles and permissions based on job responsibilities to ensure that users have access only to the data they require for their tasks. Regularly review and update access privileges to reflect changes in personnel roles or project requirements.
2. Encryption at Rest and Transit: Employ encryption to protect data at rest and during transmission. Use robust encryption algorithms like Advanced Encryption Standard (AES) for data storage and Secure Sockets Layer (SSL) or Transport Layer Security (TLS) for secure data transmission between systems. Encryption ensures data remains unintelligible even if unauthorized access occurs.
3. Regular Security Audits and Penetration Testing: Conduct regular security audits to identify weaknesses and potential security gaps. Engage in penetration testing to simulate real-world attack scenarios and identify weaknesses in your data warehouse’s defenses. Regular assessments help you avoid possible threats and take strong measures to address them proactively.
4. Data Masking and Anonymization: For non-production environments or when sharing data with third parties, consider implementing data masking or anonymization techniques. This process replaces sensitive data with realistic but fictional data, ensuring that privacy is maintained while still allowing data to be used for development, testing, or analytics.
5. Secure Data Integration and ETL Processes: Implement secure data integration practices to ensure that data flowing into your warehouse is not compromised. Secure Extract, Transform, Load (ETL) processes using encryption and secure connections to prevent data leaks during data movement. Verify the data sources to avoid malicious or compromised data from entering the warehouse.
6. Data Governance and Compliance Policies: Develop and enforce data governance policies that outline data ownership, retention, and usage guidelines. Align your data practices with industry regulations such as GDPR, HIPAA, or industry-specific compliance standards. Implement automated tools to monitor and enforce compliance, generating alerts for policy violations.
7. User Training and Awareness: Invest in regular training for employees and users who interact with the data warehouse. Educate them about security best practices, such as creating strong passwords, recognizing phishing attempts, and following proper data handling procedures. A well-informed workforce is your first line of defense against security breaches.
8. Implement Data Loss Prevention (DLP) Measures: Deploy data loss prevention solutions that monitor and control data leaving your organization’s network. DLP solutions can detect and prevent unauthorized transfers of sensitive data, ensuring that critical information remains within the organization’s control.
9. Regular Backup and Disaster Recovery Planning: Regularly back up your data warehouse to ensure availability and quick recovery in case of data breaches or disasters. Develop a comprehensive disaster recovery plan that outlines steps to take in case of data loss or system compromise. Regularly test and update your disaster recovery plans to guarantee their effectiveness.
10. Collaboration with Cybersecurity Experts: Engage with cybersecurity experts specializing in data warehousing and cloud security. Their expertise can provide valuable insights, recommendations, and guidance to help your enterprise stay ahead of emerging security threats and challenges.

Conclusion: A strong defense for data assets 

Data security and governance within data warehousing play a critical role in safeguarding an organization’s data assets. A robust security strategy and effective governance practices ensure data integrity, authorized access, and adherence to regulations. By adopting these practices and drawing insights from practical examples, organizations can confidently manage data within the complex landscape of modern data warehousing. 

 

Written by Ovais Naseem

Can AI in cybersecurity help defend against evolving threats? Yes. The need to safeguard networks, systems, and data from diverse threats, such as malware, phishing, and ransomware, has never been more urgent.

The rise of artificial intelligence (AI) offers a ray of hope. AI is rapidly transforming various industries, leveraging the power of computers to mimic human intelligence, learn, reason, and make informed decisions.

Together, let’s delve into the world of AI in cybersecurity, exploring how this cutting-edge technology is revolutionizing threat detection and response. As we navigate the potential biases, risks, and ethical considerations, we’ll also uncover the promising future prospects of AI in safeguarding our digital realm.

AI in cybersecurity: Bolstering defense mechanisms against cyber threats

1. Proactive threat detection:

AI can analyze vast amounts of data in real-time, spotting anomalies and potential threats with high accuracy. This is because AI can learn patterns in data that humans cannot, and it can identify threats that may be missed by traditional security tools. For example, AI can be used to analyze network traffic to identify suspicious patterns, such as a large number of connections from a single IP address.

2.Automated incident response:

AI can automate incident handling, minimizing damage and enabling quick recovery. This is because AI can quickly identify and respond to threats, without the need for human intervention. For example, AI can be used to automatically quarantine infected devices, or to roll back changes that were made by a malicious actor.

3. Behavioral analysis & user monitoring:

AI can detect suspicious user activities, protecting against insider threats. This is because AI can learn normal user behavior, and it can identify deviations from that behavior. For example, AI can be used to detect if a user is trying to access sensitive data from an unauthorized location.

4. Threat intelligence and prediction:

AI can process threat intelligence data to predict and prevent potential threats. This is because AI can learn about known threats, and it can use that knowledge to identify potential threats that may not yet be known. For example, AI can be used to predict which systems are most likely to be targeted by a particular threat actor.

5. Anomaly-based intrusion detection:

AI can detect deviations from normal behavior, identifying zero-day attacks. This is because AI can learn normal behavior, and it can identify deviations from that behavior. For example, AI can be used to detect if a system is behaving abnormally, which could be a sign of a zero-day attack.

6. Enhanced phishing detection:

AI can analyze emails and URLs to distinguish phishing attempts from legitimate communications. This is because AI can learn about the characteristics of phishing emails and URLs, and it can use that knowledge to identify phishing attempts. For example, AI can be used to detect if an email is coming from a suspicious sender, or if a URL is pointing to a malicious website.

Cybersecurity for threat detection, analysis, and response

AI is used in cybersecurity for a variety of purposes, including:

• Threat detection: AI can be used to detect cyber threats more quickly and accurately than traditional methods. This is done by using machine learning to analyze large amounts of data and identify patterns that may indicate a potential attack.
• Threat analysis: AI can be used to analyze cyber threats in order to understand their nature and impact. This information can then be used to develop effective mitigation strategies.
• Threat response: AI can be used to respond to cyber threats more quickly and effectively. This is done by using machine learning to identify and block malicious traffic, as well as to automate the process of incident response.
• Network Traffic Analysis: AI identifies malicious activities hidden in legitimate network traffic.

Examples of AI-powered cybersecurity tools and applications

There are a number of AI-powered cybersecurity tools and applications available, including:

• CrowdStrike Falcon: CrowdStrike Falcon is an AI-powered cybersecurity platform that provides threat detection, analysis, and response capabilities.
• Palo Alto Networks Cortex XDR: Palo Alto Networks Cortex XDR is an AI-powered cybersecurity platform that provides comprehensive visibility and control over your entire IT environment.
• IBM Security QRadar with Watson: IBM Security QRadar with Watson is an AI-powered cybersecurity platform that provides threat intelligence, analytics, and automation.

 

Read more –> Top 6 cybersecurity trends to keep an eye on in 2023

 

AI-Driven Threat Detection

Traditional threat detection methods have been effective to some extent, but they face several challenges and limitations. One significant challenge is the sheer volume of data generated by modern networks and systems, making it difficult for human analysts to manually identify potential threats in real-time.

Additionally, cyber threats are becoming increasingly sophisticated and can easily evade rule-based detection systems. Traditional methods may struggle to keep up with rapidly evolving attack techniques, leaving organizations vulnerable to advanced threats.

Moreover, false positives and false negatives can hamper the accuracy of threat detection, leading to wasted time and resources investigating non-threatening incidents or missing actual threats.

Threat detection: Advanced pattern recognition and anomaly detection

AI-driven threat detection systems leverage machine learning algorithms to overcome the limitations of traditional methods. These systems can analyze vast amounts of data in real-time, detecting patterns and anomalies that may signify potential security breaches.

AI algorithms can learn from historical data and adapt to new threats, making them highly effective in identifying previously unseen attack vectors. The ability to detect unusual patterns and behaviors, even without explicit rules, allows AI-powered systems to uncover zero-day attacks and other advanced threats that traditional methods might miss.

Real-world examples: AI detecting cyber threats

• Network Intrusion Detection: AI-driven intrusion detection systems can monitor network traffic, identify suspicious activities, and detect intrusions from various attack vectors like malware, phishing attempts, and brute-force attacks.
• Behavioral Analysis: AI algorithms can analyze user behavior and identify deviations from normal patterns, enabling the detection of insider threats or compromised accounts.
• Advanced Malware Detection: AI can recognize previously unknown malware patterns and behaviors, facilitating early detection and containment.

AI-powered security analytics

AI in processing and analyzing vast amounts of security data

AI plays a crucial role in security analytics by processing and analyzing large volumes of data generated from different sources, such as logs, network traffic, user activity, and endpoint events. The algorithms can quickly sift through this data to identify potential security incidents, anomalies, and trends. This automated analysis significantly reduces the workload on human analysts and enables faster responses to emerging threats.

How AI-Driven analytics helps in identifying potential vulnerabilities

AI-driven analytics can identify potential vulnerabilities and weak points in an organization’s security posture by continuously monitoring and assessing the IT environment. The algorithms can detect configuration errors, outdated software, and misconfigurations that may create security gaps.

By correlating data from multiple sources, AI analytics can provide a holistic view of the security landscape and prioritize critical vulnerabilities, allowing security teams to address them proactively.

Case Studies of AI-Based security analytics

• Incident Response Automation: AI-powered security analytics can automate incident response by detecting threats, assessing their severity, and triggering appropriate responses. This helps in containing threats before they escalate, reducing response times, and minimizing potential damage.
• Threat Hunting: AI algorithms can assist security analysts in threat hunting activities by flagging suspicious patterns and highlighting potential threat indicators, making the hunt more efficient and effective.
• Predictive Security: By analyzing historical data, AI-driven security analytics can predict potential security threats and vulnerabilities, allowing organizations to take preventive measures to strengthen their defenses.

AI in incident response and mitigation

Traditional incident response is a manual process that can be time-consuming and error-prone. It typically involves the following steps:

• Detection: Identifying that an incident has occurred.
• Containment: Isolating the affected systems and preventing further damage.
• Investigation: Determining the root cause of the incident.
• Remediation: Fixing the vulnerability that allowed the incident to occur.
• Recovery: restoring the affected systems to their original state.

AI-driven incident response automates and accelerates many of these steps. This can help organizations to reduce response time and minimize damage.

How AI automates and accelerates incident detection, containment, and recovery

AI can be used to automate and accelerate incident detection in a number of ways. For example, AI can be used to monitor network traffic for malicious activity. It can also be used to analyze user behavior for signs of compromise.

Once an incident has been detected, AI can be used to automate the process of containment. This can involve isolating the affected systems and blocking malicious traffic.

AI can also be used to automate the process of recovery. This can involve restoring the affected systems to their original state and implementing mitigation measures to prevent future incidents.

 

Read more –> Top 6 cybersecurity trends to keep an eye on in 2023

 

Challenges and risks of AI in cybersecurity

Artificial Intelligence (AI) has shown great promise in enhancing cybersecurity, but it also comes with its own set of challenges and risks that need to be addressed. As AI becomes more prevalent in cybersecurity practices, organizations must be aware of the following potential pitfalls:

Potential biases and limitations of AI algorithms

AI algorithms are only as good as the data they are trained on, and if this data contains biases, the AI system can perpetuate and amplify those biases. For example, if historical data used to train an AI cybersecurity model is biased towards certain types of threats or attackers, it might overlook emerging threats from different sources. Ensuring diversity and inclusivity in training data and regularly auditing AI systems for biases are crucial steps to mitigate this risk.

Moreover, AI systems have limitations in understanding context and intent, which can lead to false positives or negatives. This limitation may result in the misidentification of legitimate activities as malicious or vice versa. Cybersecurity professionals must be vigilant in interpreting AI-generated results and validating them with human expertise.

Risk of AI being exploited by cyber attackers

As AI technologies evolve, cyber attackers can exploit them to their advantage. For instance, attackers can use AI to design and execute more sophisticated attacks that evade traditional cybersecurity defenses. AI-generated deepfakes and synthetic content can also be leveraged to deceive users and penetrate security measures.

To counter this risk, organizations should focus on developing adversarial AI capabilities to identify and defend against AI-driven attacks. Additionally, ongoing monitoring and updating of AI models to stay ahead of potential malicious use are essential.

Ethical considerations in using AI for cybersecurity

AI-driven cybersecurity raises ethical concerns, particularly regarding user privacy and surveillance. The collection and analysis of vast amounts of data to detect threats might infringe upon individual privacy rights. Striking the right balance between security and privacy is crucial to avoid violating ethical principles.

Transparency and explainability of AI algorithms are also vital in gaining user trust. Users and stakeholders need to understand how AI makes decisions and why certain actions are taken. Ethical guidelines should be established to ensure responsible AI use in cybersecurity practices.

Future prospects: AI and cybersecurity

AI’s potential in the cybersecurity domain is immense, and it opens up several opportunities for the future:

Predictions for the future of AI in the cybersecurity domain

In the future, AI is expected to become even more integral to cybersecurity. AI-driven threat detection and response systems will become increasingly sophisticated, enabling quicker identification and mitigation of cyber threats. AI will also play a significant role in automating routine security tasks, allowing cybersecurity professionals to focus on more complex challenges.

 Countering emerging threats like AI-driven attacks

As AI-driven attacks become a reality, AI will be indispensable in defending against them. AI-powered security solutions will continuously adapt to evolving threats, making it more challenging for attackers to exploit AI vulnerabilities. Proactive measures, such as ethical hacking using AI, can also help identify and rectify potential weaknesses in AI-based cybersecurity systems.

 Continuous research and development in AI for cybersecurity

The dynamic nature of cybersecurity demands continuous research and development in AI. Cybersecurity professionals and AI experts must collaborate to enhance AI models’ robustness, accuracy, and resilience. Investment in cutting-edge AI technologies and ongoing training for cybersecurity professionals are vital to stay ahead of cyber threats.

Conclusion

AI has the potential to revolutionize cybersecurity and make it more effective. By using AI, organizations can detect and respond to cyber threats more quickly and effectively, which can help to protect their networks, systems, and data from harm.

The future of cybersecurity is AI-driven. Organizations that want to stay ahead of the curve need to invest in AI-driven cybersecurity solutions.

 

The world of cybersecurity is constantly evolving, and with the rise-in-prominence of remote work and online transactions, the demand for cybersecurity professionals is higher than ever.

Fortunately, the internet has made it possible to learn about cybersecurity from anywhere through online courses. In this article, we will outline the benefits of taking a cybersecurity course online and some of the best top-ranked online cybersecurity courses available.

Best online cybersecurity courses

Cybersecurity is a growing field, and with the rise of remote work and online transactions, the demand for cybersecurity professionals has touched an all-time peak. Fortunately, the internet has made it possible to learn about cybersecurity from anywhere through online courses. In this article, let us explore the best cybersecurity courses available online.

1. Advanced Executive Program in Cybersecurity

The Advanced Executive Program in Cybersecurity offered by IIITB in partnership with Simplilearn, is an intensive program designed for cybersecurity professionals looking to advance their careers. The program covers topics such as cybersecurity strategy, risk management, and incident response.

It is taught by industry experts and includes hands-on exercises and projects to apply the knowledge learned in real-world scenarios. The program is self-paced and can easily be completed in 6 months. Upon completion, graduates will receive a certificate from IIITB, which is recognized by industry leaders.

The program is an excellent option for cybersecurity professionals looking to enhance their cybersecurity and ethical hacking skills and advance their careers.

2. Harvard’s Cybersecurity: Managing Risk in the Information Age

This course is offered through edX and is taught by Harvard professors. The course covers topics such as risk management, cryptography, and cybersecurity regulations. The course is self-paced and takes about 6-10 weeks to complete. The course is free, but a certificate of completion can be obtained for a fee.

3. Post Graduate Program in Cyber Security by MIT Schwarzman College of Computing

The Post Graduate Program in Cyber Security offered by the MIT Schwarzman College of Computing in partnership with Simplilearn is an advanced program designed for professionals looking to deepen their knowledge of cybersecurity.

The program covers topics such as network security, cryptography, and cybersecurity risk management. It is taught by industry experts and includes hands-on exercises and projects to apply the knowledge learned in real-world scenarios. The program is self-paced and can be completed in 6 months.

Graduates receive a certificate from the MIT Schwarzman College of Computing, which industry leaders recognize. The program is an excellent option for professionals looking to advance their careers in cyber security.

4. Stanford’s Cybersecurity Graduate Certificate

This certificate program is offered through the Stanford Center for Professional Development and covers topics such as network security, cryptography, and secure coding practices. The program is self-paced and takes about 1-2 years to complete. The program is designed for working professionals and is taught by experts in the field. The program includes online lectures, assignments, and exams.

5. Cyber Security Expert Master’s program from Simplilearn

The Cyber Security Expert master’s program offered by Simplilearn is a comprehensive program designed for professionals looking to gain expertise in cyber security. The program covers topics such as network security, cryptography, cyber forensics, and incident response.

It is taught by industry experts and includes hands-on exercises and projects to apply the knowledge learned in real-world scenarios. The program is self-paced and can be completed in 12 months. Graduates receive a master’s certificate in cyber security, which industry leaders recognize.

The program is an excellent option for professionals looking to specialize in cybersecurity and advance their careers in this field.

6. Udacity’s Introduction to Cybersecurity Nanodegree Program

This program is designed for beginners and covers topics such as network security, cryptography, and security compliance. The program is self-paced and takes about 3 months to complete. The program includes online lectures, projects, and mentorship from industry experts. The program also includes a career services component to help graduates find employment in the field.

7. SANS Cybersecurity Training

SANS offers a variety of cybersecurity courses online, covering topics such as ethical hacking, digital forensics, and incident response. The courses are self-paced and include online lectures, hands-on exercises, and exams. The courses are taught by experts in the field and are designed for individuals at all levels of expertise. The courses range in length from a few days to several months.

8. Cybrary’s Cybersecurity Career Pathways

This program is designed for individuals looking to start a career in cybersecurity. The program covers topics such as network security, ethical hacking, and digital forensics. The program is self-paced and includes online lectures, hands-on exercises, and exams. The program is taught by industry experts and includes a career services component to help graduates find employment in the field.

9. Data Science Dojo’s Cybersecurity course

Data Science Dojo’s cyber security course can help professionals and businesses protect their digital life within a 4-hour comprehensive session. The attendees will learn to safeguard their online activities, secure their devices, and defend against scams. Taught by a veteran cybersecurity leader, this course requires no advanced skills required. and is suitable for individuals and teams.

10. Professional Certificate Program in Ethical Hacking and Penetration Testing

IIT Kanpur’s Professional Certificate Program in Ethical Hacking and Penetration Testing, offered in partnership with Simplilearn, is a comprehensive program designed for professionals looking to learn about ethical hacking and penetration testing.

The program covers topics such as vulnerability assessment, network penetration testing, and ethical hacking techniques. The program is self-paced and can be completed in 6 months. It is taught by industry experts and includes hands-on exercises and projects to apply the knowledge learned in real-world scenarios.

Graduates receive a certificate from IIT Kanpur, which is recognized by industry leaders. The program is an excellent option for professionals looking to gain skills in ethical hacking and penetration testing.

Benefits of taking a cyber-security course online

• Flexibility – One of the main benefits of taking a cyber security course online is the flexibility it offers. Students can learn the topics at their own pace, on their own schedule, and from anywhere with an internet connection. This is particularly useful for working professionals or those with other commitments that make attending traditional classes difficult.

 

• Access to expertise – Online courses often bring together experts from around the world to provide instruction and guidance. Students can learn from the best in the field, regardless of their geographic location.

 

• Lower costs – Online courses are generally more affordable than traditional classroom-based courses. This is because there are no facility costs, no travel expenses, and no need for physical textbooks or course materials.

 

• Wide range of courses – Online courses offer a wider range of cybersecurity courses than traditional classroom-based courses. Students can choose from courses that cover topics such as network security, cybercrime, cryptography, and more.

Conclusion

Cybersecurity is a rapidly growing field, and with the increasing demand for skilled professionals, taking a cybersecurity course online can help individuals gain the skills and knowledge necessary to succeed. Online courses offer flexibility, access to expertise, lower costs, and a wide range of courses to choose from. With so many options available, individuals can choose the program that best suits their needs and schedule.

 

Written by Faiz Muhammad

Are you looking to optimize your IT infrastructure and streamline your deployment processes? It might be time to consider upgrading your System Center Configuration Manager (SCCM) infrastructure. With the latest version of SCCM, you can take advantage of new features that enhance security, improve performance, and simplify device management.   

In this article, we’ll explore the benefits of upgrading to SCCM and how it can improve your organization’s productivity. From faster software deployments to more efficient patching solutions, an SCCM upgrade could be just what you need to take your IT operations to the next level. So let’s dive in and discover all the advantages an SCCM upgrade has to offer. 

Why an SCCM infrastructure upgrade is essential ?

An SCCM infrastructure upgrade is a must-have for organizations that are looking to improve the efficiency and productivity of their IT department. With the latest version of SCCM, organizations can enjoy features such as better endpoint management, streamlined patching, and updating procedures, improved compliance with regulatory requirements, enhanced reporting capabilities, and more. 

One of the standout benefits of an SCCM infrastructure upgrade is its ability to reduce operational costs. With a centralized management system in place, IT departments can save time and resources by automating manual processes such as software distribution and updates. Additionally, this automated process ensures that all endpoints are up-to-date with patches and security updates reducing vulnerabilities. 

By upgrading their SCCM infrastructure, organizations also benefit from an improved level of security. The advanced tools available in the latest version allow administrators to identify vulnerabilities on endpoints so they can be quickly remediated before they cause a breach or data loss. This proactive approach helps organizations maintain compliance with industry regulations while keeping sensitive data safe from cyber threats. 

Improved security

An SCCM infrastructure upgrade can deliver improved security for organizations. One of the benefits is the ability to control and manage access to resources across an organization’s network. With SCCM, IT teams can define user roles and give them specific permissions based on their job functions. This not only ensures that users have access only to what they need but also reduces the risk of unauthorized access or data breaches. Additionally, SCCM allows IT teams to monitor endpoints for vulnerabilities and apply security patches remotely. 

Another benefit of an SCCM infrastructure upgrade is its ability to automate security processes. For instance, it can automatically scan devices for malware or other security threats and flag them for remediation. This ensures that devices are always up-to-date with the latest security patches, reducing the risks associated with outdated software. 

Overall, an SCCM infrastructure upgrade provides organizations with a comprehensive solution that enhances their cybersecurity posture while reducing operational costs associated with managing endpoints manually. By leveraging automation and centralized management capabilities, organizations can achieve better visibility into their networks while keeping sensitive information safe from cyber threats. Learn Pega Training to improve your business skills.  

Protect your network from cyber threats 

An SCCM infrastructure upgrade is a crucial step toward protecting your network from cyber threats. With the ever-increasing sophistication of cyber attacks, it is essential to have an up-to-date and robust system in place that can detect and neutralize potential threats. An SCCM upgrade provides you with enhanced security features such as advanced threat analytics, endpoint protection, and compliance management. These features work together to keep your network safe and secure. 

One of the main benefits of an SCCM infrastructure upgrade is improved visibility into your network. This visibility allows you to identify potential vulnerabilities and take prompt action before they can be exploited by cybercriminals. Additionally, an upgraded SCCM system enables you to implement stricter access control policies for users, devices, and applications on your network. 

Overall, investing in an SCCM infrastructure upgrade is a proactive measure that helps safeguard your business against cyber threats. With advanced security features such as threat detection and compliance management at your disposal, you can rest easy knowing that your network is protected from the latest security risks. 

Enhanced efficiency

Enhanced efficiency is a critical aspect of any organisation’s success. One way to improve your team’s productivity and effectiveness is by upgrading your SCCM infrastructure. With the latest version of SCCM, you can streamline the software deployment process, automate device management, and provide remote assistance to end-users efficiently. 

By leveraging SCCM’s advanced features like task sequencing, you can minimize manual intervention during deployments and improve accuracy. Additionally, with real-time monitoring capabilities provided by the new SCCM release, you can proactively detect potential issues before they become major problems that disrupt your operations. 

An upgraded SCCM infrastructure also enables you to manage devices from a single console seamlessly. This feature reduces the complexity in managing multiple devices across different locations within your organization. Moreover, it improves overall visibility into device performance and security compliance metrics that are crucial for maintaining efficient operations. By investing in an updated SCCM infrastructure, organizations can benefit from improved efficiency levels across various departments, leading to better business outcomes over time. 

Automate management and deployment processes 

Upgrading your SCCM infrastructure can bring a host of benefits to your organization, particularly when it comes to automating management and deployment processes. With an upgraded SCCM infrastructure, you can streamline the process of deploying software updates and patches, ensuring that your systems are always up-to-date with the latest security protocols. This can help to reduce the risk of cyberattacks and improve overall system performance. 

Furthermore, an upgraded SCCM infrastructure can also enable more efficient management of devices within your organization. With automated device enrollment and configuration management capabilities, you can ensure that all devices are configured consistently and in line with organizational policies. This not only saves time but also helps to reduce errors and inconsistencies across your device fleet. 

Finally, upgrading your SCCM infrastructure can provide greater visibility into device status and usage across your organization. By leveraging advanced reporting tools, you gain insights into how devices are being used and where resources may be underutilized or overused. This information is invaluable for optimizing resource allocation and improving overall productivity within your organization. 

Get real-time visibility into your network 

An SCCM infrastructure upgrade can significantly improve real-time visibility into your network, allowing you to track the health and status of your devices in real-time. With an upgraded SCCM infrastructure, you can monitor every endpoint on your network from a single pane of glass dashboard, giving you a comprehensive view of device performance. 

Real-time visibility enables proactive troubleshooting and increases system up-time by identifying issues before they become serious problems. It also allows IT teams to quickly identify the root cause of any performance issues and resolve them promptly. 

In addition, real-time visibility provides insights into how employees are using their devices and what applications they are running. This information can be used to optimize resource utilization, manage software licenses more effectively, and enhance overall security posture. Ultimately, gaining real-time visibility is essential for IT professionals looking to keep their networks running smoothly while ensuring that all endpoints remain secure against potential threats. 

Cost savings

An SCCM infrastructure upgrade is a wise investment that can lead to significant cost savings for businesses. By streamlining IT operations, reducing downtime and minimizing support costs, an SCCM infrastructure upgrade can help organizations improve their bottom line. With better visibility into software and hardware assets, IT staff can make more informed decisions about which systems need upgrades or replacements. 

Moreover, an SCCM infrastructure upgrade allows organizations to automate routine tasks such as patch management and software deployment. This means less time spent on manual updates and more resources directed toward strategic initiatives that drive business growth. Additionally, the centralized management of endpoint devices decreases the risk of security breaches caused by unpatched vulnerabilities. 

The benefits of an SCCM infrastructure upgrade go beyond cost savings; it also improves employee productivity and satisfaction. With faster response times from IT staff due to streamlined operations, employees experience fewer interruptions in their workday leading to increased job satisfaction and improved morale. Ultimately, investing in an SCCM infrastructure upgrade is a smart move for businesses looking to optimize their IT efficiency while keeping costs down. 

Simplify IT operations and reduce workload

An SCCM infrastructure upgrade provides numerous benefits to an organization such as simplified IT operations and reduced workload. It streamlines the management of devices, applications, updates, and security policies across the enterprise network. With SCCM’s unified platform for endpoint management, administrators can automate routine tasks like software updates and patches that would otherwise consume a significant amount of time. 

Furthermore, SCCM enables organizations to proactively monitor their systems’ health status and identify potential issues before they escalate into major problems. This proactive approach minimizes downtime and helps ensure optimal network performance. Additionally, with centralized reporting capabilities, administrators can quickly generate reports on hardware inventory, software usage patterns, compliance status, and more. 

In conclusion, upgrading your SCCM infrastructure delivers significant benefits that improve your organization’s overall efficiency while reducing the IT team’s workload. By automating routine tasks like software updates and patching through a unified platform for endpoint management across your enterprise network with SCCM you can free up resources to focus on business-critical projects that drive growth. 

Conclusion

In conclusion, upgrading your SCCM infrastructure can bring numerous benefits to your organization. First and foremost, it will improve the efficiency of your IT department by allowing them to manage devices more effectively and with greater automation. This results in less manual input, freeing up staff time for other important tasks. 

Additionally, an upgraded SCCM infrastructure provides better security measures that can protect against potential breaches or cyber-attacks. It allows the IT team to monitor activity on all connected devices more closely and respond quickly if any suspicious behavior is detected. 

Finally, an upgraded SCCM infrastructure can also lead to cost savings in the long run. Streamlining processes and automating certain tasks, it reduces the need for additional staff or resources. It also helps avoid costly downtime caused by device failures or other issues that may arise due to outdated software. 

Overall, investing in an upgrade of your SCCM infrastructure is a wise decision for any organization looking to improve its operational efficiency while ensuring maximum security and cost-effectiveness.

 

Written by Pooja Bavireddy

In the modern digital age, big data serves as the lifeblood of numerous organizations. As businesses expand their operations globally, collecting and analyzing vast amounts of information has become more critical than ever before.

However, this increased reliance on data also exposes organizations to elevated risks of cyber threats and attacks aimed at stealing or corrupting valuable information. It raises a need for big data protection.

To counter these risks effectively, content filtering, network access control, and Office 365 security services emerge as valuable tools for safeguarding data against potential breaches. This article explores how these technologies can enhance data security in the era of big data analytics. 

Importance of data privacy in the age of big data analytics 

In the era of big data analytics, data privacy has attained unprecedented importance. With the exponential growth of internet connectivity and digital technologies, protecting sensitive information from cyber threats and attacks has become the top priority for organizations.

The ramifications of data breaches can be severe, encompassing reputational damage, financial losses, and compliance risks. To mitigate these risks and safeguard valuable information assets, organizations must implement robust data protection measures.

Content filtering, network access control, and security services play pivotal roles in detecting potential threats and preventing them from causing harm. By comprehending the significance of data privacy in today’s age of big data analytics and taking proactive steps to protect it, organizations can ensure business continuity while preserving customer trust.  

Understanding content filtering and its role in big data protection 

Content filtering is critical in data protection, particularly for organizations handling sensitive or confidential information. This technique involves regulating access to specific types of content based on predefined parameters such as keywords, categories, and website URLs.

By leveraging content filtering tools and technologies, companies can effectively monitor inbound and outbound traffic across their networks, identifying potentially harmful elements before they can inflict damage. 

Content filtering empowers organizations to establish better control over the flow of information within their systems, preventing unauthorized access to sensitive data. By stopping suspicious web activities and safeguarding against malware infiltration through emails or downloads, content filtering is instrumental in thwarting cyberattacks.  

Moreover, it provides IT teams with enhanced visibility into network activities, facilitating early detection of potential signs of an impending attack. As a result, content filtering becomes an indispensable layer in protecting digital assets from the ever-evolving risks posed by technological advancements. 

Network Access Control: A key component of cybersecurity 

Network Access Control (NAC) emerges as a critical component of cybersecurity, enabling organizations to protect their data against unauthorized access. NAC solutions empower system administrators to monitor and control network access, imposing varying restrictions based on users’ roles and devices. NAC tools help prevent external hacker attacks and insider threats by enforcing policies like multi-factor authentication and endpoint security compliance.

Effective network protection encompasses more than just perimeter defenses or firewalls. Network Access Control complements other cybersecurity measures by providing an additional layer of security through real-time visibility into all connected devices.

By implementing NAC, businesses can minimize risks associated with rogue devices and shadow IT while reducing the attack surface for potential breaches. Embracing Network Access Control represents a worthwhile investment for organizations seeking to safeguard their sensitive information in today’s ever-evolving cyber threats landscape. 

Leveraging Office 365 security services for enhanced data protection 

Leveraging Office 365 Security Services is one-way businesses can enhance their data protection measures. These services offer comprehensive real-time solutions for managing user access and data security. With the ability to filter content and limit network access, these tools provide an extra defense against malicious actors who seek to breach organizational networks.

Through proactive security features such as multi-factor authentication and advanced threat protection, Office 365 Security Services enable businesses to detect, prevent, and respond quickly to potential threats before they escalate into more significant problems.

Rather than relying solely on reactive measures such as anti-virus software or firewalls, leveraging these advanced technologies offers a more effective strategy for protecting your sensitive information from breaches or loss due to human error.

Ultimately, regarding securing your valuable data from hackers or cybercriminals in today’s age of big data analytics, relying on content filtering, and network access control techniques combined with leveraging Office 365 Security Services is key.

By investing in constant updates for such technology-driven approaches related to security, you could ensure no privacy violation occurs whilst keeping sensitive files & proprietary business information confidential & secure at all times! 

Benefits of big data analytics for data protection 

The role of big data analytics in protecting valuable organizational data cannot be overstated. By leveraging advanced analytics tools and techniques, businesses can detect vulnerabilities and potential threats within vast volumes of information. This enables them to develop more secure systems that minimize the risk of cyberattacks and ensure enhanced protection for sensitive data.

One effective tool for safeguarding organizational data is content filtering, which restricts access to specific types of content or websites. Additionally, network access control solutions verify user identities before granting entry into the system. Office 365 security services provide an extra layer of protection against unauthorized access across multiple devices.

By harnessing the power of big data analytics through these methods, businesses can stay ahead of evolving cyber threats and maintain a robust defense against malicious actors seeking to exploit vulnerabilities in their digital infrastructure. Ultimately, this creates an environment where employees feel secure sharing internal information while customers trust that their data is safe. 

Best practices for safeguarding your data in the era of big data analytics 

The era of big data analytics has revolutionized how businesses gather, store, and utilize information. However, this growth in data-driven tools brings an increasing threat to valuable company information. Effective content filtering is key in limiting access to sensitive data to safeguard against cyber threats such as hacking and phishing attacks.

Employing network access control measures adds a layer of security by regulating user access to corporate systems based on employee roles or device compliance. Office 365 security services offer a holistic approach to protecting sensitive data throughout the organization’s cloud-based infrastructure. 

With features such as Data Loss Prevention (DLP), encryption for email messages and attachments, advanced threat protection, and multifactor authentication, Office 365 can assist organizations in mitigating risks from both internal and external sources.  

Successful implementation of these tools requires regular training sessions for employees at all organizational levels about best practices surrounding personal internet use and safe handling procedures for company technology resources. 

Ensuring data remains safe and secure 

Overall, ensuring data safety and security is vital for any organization’s success. As the amount of sensitive information being collected and analyzed grows, it becomes crucial to employ effective measures such as content filtering, network access control, and Office 365 security services to protect against cyber threats and attacks. 

By integrating these tools into your cybersecurity strategy, you can effectively prevent data breaches while staying compliant with industry regulations. In a world where data privacy is increasingly important, maintaining vigilance is essential for protecting crucial resources and ensuring the growth and competitiveness of businesses in the modern era.

 

Written by Muhammed Haseeb

In order for businesses to respond to SaaS threats efficiently and adhere to industry requirements, SSPM (SaaS security posture management) poses a vital component. But to safeguard SaaS access, SSPM is frequently insufficient, unfinished, and ineffectual. 

The explanation of SSPM (SaaS Security Posture Management) 

Businesses are increasingly embracing SaaS software to manage a variety of operations, including marketing and sales. The myriad concerns it raises for compliance and security increase as this tendency skyrockets at the same time. SaaS app usage oversight is possible with the help of SSPM. Let’s describe SSPM. The phrase describes the tools used by companies to identify, evaluate, and lower these risks.  

SaaS apps may expose users to the following threats: 

1. Issues with compliance
2. Lax rules for permitted use 
3. Unstable settings
4. Potentially still-accessible inactive users

SSPM security gives businesses the power they need to safeguard important corporate information that resides across many apps, as well as sometimes personal information.

Whether it’s a straightforward blog page or a complex e-commerce website, cybercriminals are continuously searching for new ways to harvest data from web pages and web apps. Any company’s website security, as well as subscribers’ info (many membership websites must collect recurring payments and establish several levels of member access), depends on the third-party service providers it uses.

All in all, SSPM security provides insights into prospective SaaS issues that your teams could run into, allowing you to look for ways to avoid problems.

Benefits of SSPM security 

Businesses may experience serious security and regulatory repercussions if SaaS application security posture management isn’t implemented. The benefits listed below show why SSPM is essential for many organizations. 

Measures to prevent misconfigurations  

Misconfigurations provide the most significant risk to cloud security and are a factor in a large number of data breaches. Even if an app is first configured correctly by a company, later compliance issues could arise from subtle deviations.  

A company can more easily maintain safe configurations with the help of SSPM, even if apps change and clients who use them alter. 

Makes authorized use settings more robust   

Not every worker will have access to the same information, even inside a single app. If users have additional permissions in an app than they have been granted, SSPM looks at the resources to find out.  

By ensuring that only individuals who are authorized can access and modify the data, this feature improves data security. 

Optimizes compliance  

SaaS solutions have increased the complexity of compliance management. By constantly comparing safety practices with internal frameworks and industry standards, SSPM overcomes these difficulties.  

Despite the significant advantages of SSPM, posture management may be a very challenging procedure for both small and large businesses. As a result, SSPM security faces a number of difficulties, such as: 

• Managing a variety of apps: Configuration, data transfer, and other similar tasks may be approached differently by various apps. Effective security requires the time-consuming effort of going over each one.  
• Finding security features in each configuration requires businesses to navigate a variety of app interfaces, and these features may appear differently in each app. Simple operations, like allowing staff to use specific apps, could become ineffective as a result.  
• Taking action in the face of configuration drift: Setting up an app just once rarely suffices because it can deviate from the original configuration, opening the door for security issues if left unchecked. 

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Why SSPM Is insufficient 

Even though SSPM may be helpful for businesses, it’s an inadequate security strategy since it ignores the ever-changing character of SaaS systems. Administrators can only find issues with SSPM when certain settings are met. They are not given any assistance in figuring out who utilizes these apps or how they are used. 

Furthermore, only a few applications, including Slack, Microsoft Office 365, and Salesforce are frequently supported by SSPM systems. Because of this, businesses find it challenging to rely entirely on SSPM for SaaS resources. 

SaaS Security Control Plane (SSCP) usage 

Mixing the aforementioned solution with a SaaS Security Control Plane (SSCP) may be advantageous for businesses that have solely adopted SSPM security. The SSCP must be implemented by any business that wants to protect itself against the security hazards of the modern world. Utilizing security rules for people and processes, it scans the entire SaaS architecture for hazards.  

Additionally, SSCP covers a wider range of SaaS resources, including managed and unmanaged devices as well as sanctioned and unsanctioned apps. SCCP is extremely effective and has a quick deployment time. 

SSPM vs. SSCP 

The SSCP involves setting up security throughout the entire infrastructure, as was already mentioned. This covers people, processes, and apps, in addition to technology like SSPM. It goes above and beyond the typical safeguards for widely used applications like Office 365 to keep track of all the resources a company utilizes on a regular basis.  

An SSCP’s improved capabilities enable your company to freely use apps with the knowledge that they are all secure. Additionally, it may reduce the risks that SSPM introduces when managing divergent configurations across various apps, including drift and any ensuing compliance issues. Employing SSCP in this way helps you uphold industry requirements while also enhancing your security plan. 

A new solution emerged: CSPM 

It’s crucial to assess SSPM solutions’ potential as they gain popularity in the security industry. This kind of activity is especially necessary right now since cybersecurity threats are growing and IT funds are under review. 

After all, CSPM’s (Cloud Security Posture Management’s) capacity to spot cloud network errors and safeguard your data housed in Azure, Google Cloud, AWS, and other cloud hosting alternatives can’t be replaced by SSPM. The usefulness of CSPM’s risk assessment and mitigation for enterprises with just cloud-based data storage is undeniable. But what about the information you have stored elsewhere? And all the settings in the dozens, if not hundreds, of SaaS apps that your company uses every day? 

These malware and data loss scenarios aren’t just for a cocktail party. The number of high-profile security incidents and breaches involving providers and third-party vendors continues to rise. 

The CSPM is ill-prepared to deal with evolving cybersecurity risks. You need a distinct security posture to address the SaaS application vulnerabilities, especially those that store sensitive data. 

What’s the purpose of CSPM’s monitoring and why is SaaS data not protected? 

Vendors of CSPM software keep track of the compliance and security status of both generic and specific cloud apps that are installed in public cloud environments. Additionally, they frequently offer DevOps, dynamic cloud integration, and compliance monitoring capability. 

The SaaS applications’ security posture and associated data, which is frequently the most sensitive data for a corporation, is neglected when relying just on CSPM. Because of this, enterprise applications like Microsoft 365, ServiceNow, and Salesforce are vulnerable to dangerous structures, configuration drift, and non-compliance. Additionally, the thousands of SaaS programs utilized by organizational divisions and departments make security breaches even more likely. 

How can SaaS security vulnerabilities be mitigated by SSPM? 

In SaaS applications, data security is the main focus of SSPM. It swiftly and automatically identifies app misconfigurations and associated security flaws. 

Of all, SaaS’s much-lauded adaptability is precisely what exposes businesses to a variety of security flaws and incorrect configurations. Even with security guidelines in place, modifications made in business settings are frequently not communicated to security and IT teams.  

Although it may appear to be unimportant from the viewpoint of a user or business owner, this unmonitored and undetected behavior might lead to security flaws and insecure SaaS data.

With SSPM in place, you’ll be able to stop potentially detrimental changes by knowing what changes staff members are making to apps. Your company will be able to monitor cloud-based SaaS apps like Microsoft 365, ServiceNow, Salesforce, and others automatically and continuously.

Without increasing their workloads, your security team can help ensure compliance by identifying overly permissive settings. SSPM vs. CSPM 

	CSPM	SSPM
Focus areas	Watching over cloud services like Azure, Cloud, and AWS.	Watch over SaaS and PaaS programs like ServiceNow, Microsoft 365, and Salesforce, among others. Some solutions additionally protect unique applications.
Perks	Locating incorrectly configured networks; Evaluating current data risk;  Constantly keeping an eye on cloud environments.	Controlling third-party apps  Monitoring SaaS environments continuously  Identifying SaaS configuration errors Identifying settings that are too permissive Workflows for security automation  Constantly identifying risks Offering corrective suggestions Risk compliance and governance simplification.
Cases of use	Finding dangerous cloud setup options  Ensuring security framework compliance  Monitoring cloud-based services  Managing log change management.	Continuous SaaS app access Enhancing the security posture  Integrating app and account visibility and monitoring across all SaaS providers  Fixing frequent configuration errors  Monitoring data access and privilege levels  Tally third-party applications  Monitoring and reporting on compliance
Security breach alerts	Faulty settings of data hosting;  Mistakes in permission;  Lack of MFA;  Disclosure of data storage.	Misconfigurations of SaaS  Errors with permission  Lack of MFA  Disclosure of data storage  Data breaches Internal threats  Outside hackers
Key components	Incorporating DevOps  Awareness of cloud service provider parameters Reporting Real-time activity monitoring	Securing all SaaS applications Ongoing observation  Managing data access and privilege levels Management of third-party applications  Threat recognition  DevOps Correction of configuration error Compliance

Is SSPM investment worthwhile? 

Without an SSPM tool, your company will be forced to: 

• Count on each application to protect itself. The monitoring performed by the native security tool will also be impacted if that application is ever compromised.  

• Limit security analysis and monitoring scope to native app features. Your staff will waste time monitoring dozens, and often even hundreds, of security dashboards that frequently fail to keep track of the numerous integrations that users have added. The workloads for the security team frequently increase in complexity and demand more resources. 

CISOs, CIOs, and the sector at large are now more aware of these historical security flaws. According to Gartner’s 2022 Application Security Hype Cycle, SSPM is very advantageous to businesses. Additionally, the expense and harm to one’s reputation caused by a SaaS data event much outweigh anything invested in a SaaS-focused security posture. 

Do you need SSPM, CSPM, or both for your organization? 

To completely safeguard their data and avoid configuration drift, businesses with complex tech stacks that comprise both cloud providers and several SaaS applications probably need SSPM and CSPM. 

An SSPM solution can greatly increase a security team’s productivity and completely safeguard SaaS data throughout the ever-complex SaaS application ecosystem. 

 

Written by Mahendra Bajiya

In a world where everything is just a click away, cybersecurity trends are a matter of concern. With data breaches, hacking, and malware attacks becoming more sophisticated, it’s crucial to stay ahead of the curve and remain vigilant in the fight against cybercrime. 

For the unversed, cybersecurity is the practice of protecting computer systems, networks, and data from theft, damage, or unauthorized access. In today’s digital age, cybersecurity is more important than ever, as businesses and individuals rely heavily on technology to store and exchange sensitive information. 

Key components of cybersecurity 

There are several key components to cybersecurity. The first is prevention. This involves implementing security measures such as firewalls, antivirus software, and access controls to prevent unauthorized access to systems and data. It also involves regularly updating software and systems to patch vulnerabilities that could be exploited by cybercriminals. 

Another key component of cybersecurity is detection. This involves monitoring systems and networks for suspicious activity, such as unauthorized access attempts or unusual network traffic. Early detection of potential threats can help organizations mitigate the damage and prevent data loss. 

If a breach does occur, it is important to have a response plan in place. This involves having procedures for investigating and containing the breach and notifying affected individuals and authorities as needed. It is also important to have a plan for restoring systems and data after a breach, which may involve restoring backups or rebuilding systems from scratch. 

Cybersecurity trends to watch out for in 2023 

Since cybersecurity is a constantly evolving field, new threats emerge every year. As we look ahead to 2023, there are several cybersecurity trends that organizations and individuals need to watch out for. 

 

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1. Ransomware attacks 

Ransomware is a type of malware that infects a computer system and encrypts its files, making them inaccessible to the user. The attacker then demands a ransom payment in exchange for the decryption key. 

One reason for the rise of ransomware attacks is that they are incredibly profitable for cybercriminals. The cost of paying the ransom is often much lower than the cost of restoring the system from backups or dealing with the fallout from a data breach. The consequences of a successful ransomware attack can be severe. In addition to the financial costs of paying the ransom and restoring the system, organizations may suffer reputational damage and loss of business. In some cases, sensitive data may be stolen and used for malicious purposes. 

To protect against the threat of ransomware attacks, organizations need to take proactive steps to improve their cybersecurity defenses. This includes having strong backup and recovery systems in place, regularly updating software and security patches, and educating employees about cybersecurity best practices.  

2. Healthcare sector at risk

The healthcare industry is expected to face more cyber attacks in 2023. This industry has already seen a significant increase in cyber attacks in recent years, with a 44% increase resulting in the compromise of 40 million American patient records in 2021. This affected over 22.6 million patients, which is equal to the population of New York.

A research survey shows that approximately 60% of all ransomware attacks target patient data, while the remaining attacks focus on disrupting operations or taking over systems.

Phishing scams were the most common type of cyber attack on healthcare organizations in 2020, affecting 81% of companies. With the onset of the COVID-19 pandemic, phishing incidents increased by 220%.

3. Artificial intelligence (AI) in cyberattacks  

With Chat GPT storming the internet, cybercriminals are well versed with current trends and are using Artificial intelligence to launch more sophisticated attacks. AI-powered attacks can quickly adapt to changing environments, making them harder to detect and defend against. 

AI-powered attacks can take different forms, such as phishing emails, malware, or social engineering scams. For example, AI can be used to create highly convincing phishing emails that appear to be from trusted sources, making it easier for attackers to trick users into clicking on malicious links or downloading malware. 

To protect against AI-powered cyberattacks, organizations need to stay vigilant and adopt advanced cybersecurity tools and techniques that can detect and respond to these threats in real time. This includes using AI-based cybersecurity solutions that can identify and block attacks before they cause damage. Organizations should also implement security awareness training programs to educate employees on how to recognize and report suspicious activity. 

4. IoT vulnerabilities

Next up on the cybersecurity trends list, we have IoT vulnerabilities. The security of IoT devices is a concern, and manufacturers are aware of this issue. However, they may not be fully knowledgeable about all the possible vulnerabilities that exist. If any security breaches are discovered, the consequences could be severe.

As per information from Oracle, the number of connected IoT devices has already exceeded 7 billion and is projected to increase to 22 billion by 2025. This growth presents a large opportunity for cybercriminals to carry out attacks.

5. Users as an attack surface

In 2023, one of the cybersecurity trends is expected to be the increased focus on users as an attack surface. Cyber attackers will continue to target an organization’s user base by using tactics like phishing, social engineering, and other methods to gain unauthorized access.

This trend is driven by the fact that user error remains one of the biggest cybersecurity risks for organizations, as attackers exploit the human element to gain entry to networks and systems. As a result, organizations will need to prioritize user education and awareness training to mitigate the risks posed by user-targeted attacks.

6. Quantum cryptography

As quantum computing becomes more widespread, traditional cryptographic methods used for encryption are becoming increasingly vulnerable. Quantum cryptography provides an alternative approach to encryption that is highly secure and resistant to attacks by quantum computers. Quantum cryptography uses quantum mechanics to generate encryption keys, which are then used to secure communications. This method provides an exceptionally high level of security and privacy.

Navigating cybersecurity challenges: Lessons learned and outlook 

Overall, cybersecurity is a critical component of modern business and personal life. It requires ongoing vigilance and attention, as cybercriminals continue to develop new tactics and strategies to exploit vulnerabilities. By staying informed and taking proactive measures to protect systems and data, individuals and organizations can help ensure their safety and security in the digital age. 

In conclusion, 2023 is expected to bring new and evolving cybersecurity trends and threats. It is important for organizations to stay vigilant, stay up to date with the latest cybersecurity tools and techniques, and ensure that their employees are trained to recognize and respond to potential threats. By taking proactive measures to protect their systems and data, organizations can reduce the risk of cyberattacks and keep their businesses running smoothly. 

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With Microsoft Hyper-V gaining more market share and coming of age, VMware administrators must administer Hyper-V alongside vSphere in their environments. There are certainly similarities in administering the various hypervisors, including VMware and Hyper-V, but there are also subtle differences as well. Often, out of habit, we apply what we know to things that we do not know or that are new to us.

While certain methodologies or best practices extend past the boundaries of VMware vSphere and apply to Hyper-V as well, there are differences in the administration and management of Hyper-V that VMware administrators will want to note and understand. These differences also can affect backup processes in the administration. 

Let’s take a look at some of the key differences between Hyper-V and VMware and how these can affect your backup methodologies. 

VMware vCenter Server vs. System Center Virtual Machine Manager (SCVMM)  

VMware administrators are familiar with the well-known VMware vCenter Server – a centralized management and administration tool for creating, configuring, and interacting with all aspects of the vSphere environment. From vCenter, administrators can configure and control ESXi hosts, datacenters, clusters, traditional storage, software-defined storage, traditional networking, software-defined networking, and all other aspects of the vSphere architecture. In fact, vCenter Server is a necessary component to unlock most of the enterprise-level features and functionality of VMware vSphere. 

As a VMware administrator, you will typically connect your data protection solution to VMware vCenter Server as the central management pane to back up virtual machines residing on managed ESXi hosts. This provides a central login for managing and controlling the resources backed up by vSphere data protection solutions. Moreover, you can use the HTML 5-based vSphere Web Client to manage vSphere functions from any browser. 

In Microsoft Hyper-V, the equivalent solution for managing hosts and clusters is the System Center Virtual Machine Manager, or SCVMM. 

However, with Hyper-V, you can perform many of the “enterprise” level tasks, such as managing a Hyper-V cluster, setting up high availability, and performing live migration without using SCVMM. You can use the Failover Cluster Management console to manage your cluster resources, including setting up and configuring Clustered Shared Volumes (or CSVs). Also, without SCVMM licensing, you can use the Manager console to manage each host, etc. 

Understanding the management interface and the differences between VMware vSphere and Microsoft Hyper-V is key to understanding the point of administration that is used to interface with data protection solutions, like . Typically, in either the VMware vSphere or Microsoft Hyper-V environment, you want to back up resources at the “host” level, which means you are backing up virtual machines centrally rather than from within the guest operating system. Knowing the respective management interfaces ensures effective and efficient VMware vSphere and Hyper-V backup. 

vSphere Cluster vs. Hyper-V Cluster 

With vCenter Server in place, creating a VMware vSphere ESXi cluster is a very quick and simple process: you simply add the hosts into the cluster. VMware “clustering” is purely for virtualization purposes. 

Clustering is built on top of the Windows Failover Cluster technology. Windows Failover Clustering is applied in a number of different use cases, including file servers and SQL clusters, as well as Hyper-V. Due to the more general nature of the underlying clustering technology for Hyper-V, it brings more complexity to configuring a Hyper-V virtualization cluster. However, the task can be accomplished relatively quickly if you use either PowerShell or the cluster creation wizard – Failover Cluster Manager. 

There are many data protection solutions available today that are able to easily interact with vSphere vCenter and the clusters managed therein. However, there are fewer data protection solutions that are able to integrate just as seamlessly with a cluster configuration. 

Understanding VMware VMFS and Hyper-V cluster shared volumes 

VMware vSphere utilizes the Virtual Machine File System (VMFS) – VMware’s clustered file system that was purpose-built from the ground up as a virtualization file system. With each release of vSphere, VMFS has been tweaked, and its functionality and capabilities have been extended. With vSphere 6.5, VMware introduced VMFS 6.0, featuring support for 4K Native Devices in 512e mode and automatic “unmapping” functionality to reclaim unused blocks. 

Administrators need to understand the capabilities of each type of virtualization file system. Not all data protection solutions support Microsoft Hyper-V Cluster Shared Volumes, so it is important to understand the requirements for today’s Hyper-V environments and the compatibility requirements of CSVs. 

VMware uses Snapshots; Hyper-V uses checkpoints 

Both have mechanisms that enable them to quickly save the state and data of a virtual machine at a given point in time. The term “snapshot” is by far the popularized word for this functionality and was coined by VMware. A snapshot operation in VMware creates the following files for the saved state and data: 

• .vmdk – The flat.vmdk file contains the raw data in the base disk. 
• -delta.vmdk – The delta disk is represented in the format of .00000x.vmdk. This is the differencing disk; it contains the difference between the current data of the virtual machine disk and the data at the time of the previous snapshot. 
• .vmsd – This database file contains all the pertinent snapshot information. 
• .vmsn – This contains the memory information of the virtual machine and its current state at the point in time of the snapshot. 

It uses “checkpoints” as their terminology to define the means to save a “point in time” state of a virtual machine. Let’s look at the architecture of the checkpoint. 

A Snapshots folder is created that may contain the following files: 

• VMCX – This is the new binary format for the configuration file introduced in Windows Server 2016. It replaces the XML file found in 2012 R2 and earlier. 
• VMRS – This is the state file, which contains information about the state of the virtual machine. 
• AVHDX – This is the differencing disk that is created. It records the delta changes made after the snapshot creation. 

 

As a VMware administrator, you should be advised that Microsoft has introduced “production” checkpoints with Windows Server 2016. These interact with VSS (Volume Shadow Copy) to perform checkpoints that the guest operating system is aware of. These types of checkpoints function much like backup operations performed by data protection solutions.

Importantly, Microsoft allows these “production” checkpoints to be run in production environments. This is significant because before Windows Server 2016, this technology was not supported, and it is still not supported with VMware snapshots. 

VMware changed block tracking vs. Hyper-V resilient change tracking 

With the release of ESX 4.0 back in 2009, VMware introduced a feature called Changed Block Tracking (CBT) that dramatically increases backup efficiency. Using this technology, data protection solutions are able to copy only the blocks that have changed since the last backup iteration. This method works for every backup iteration following an initial full backup of the virtual machine. You can now efficiently back up only the changes, at the block level, instead of taking full backups of a virtual machine every time, which is what generally happens with traditional legacy backup solutions.  

If you are a VMware administrator shifting to administrating Microsoft Hyper-V, you should know that Microsoft’s equivalent offering, called Resilient Change Tracking (RCT), was only introduced with Windows Server 2016.  

When you back up with Hyper-V’s Resilient Change Tracking, the following files will be created: 

• The Resilient Change Tracking (.RCT) file – a detailed representation of changed blocks on the disk (less detailed than mapping in memory). It is written in write-back or cached mode, which means that it is used during normal virtual machine operations such as migrations, startups, shutdowns, etc. 
• The Modified Region Table (.MRT) file – is a less detailed file than the (.RCT) file; however, it records all the changes on the disk. In the event of an unexpected power-off, crash, or another failure, the MRT file will be used to reconstruct the changed blocks. 

Make sure your chosen data protection solution can take advantage of the latest advancements in Hyper-V’s implementation of change tracking technology known as Resilient Change Tracking. This will ensure the quickest and most efficient Hyper-V backup iterations. 

VMware uses VMware tools; Hyper-V uses integration services 

Both VMware and Hyper-V make use of components installed in the guest operating system to ensure more powerful integration between the hypervisor and the guest operating system. In VMware vSphere, this is handled with VMware Tools.

VMware Tools is a suite of utilities that can be installed for better virtual machine performance, including driver-supported 3D graphics and mouse and keyboard enhancements, as well as time synchronization, scripting, and other automation features. Importantly, it also enables you to perform “application-aware” backups, which ensures that database applications are backed up in a transactionally consistent state. 

Concluding thoughts

In today’s world of hybrid infrastructures and multi-hypervisor environments, at some point, you will most likely be asked to act as an administrator of both VMware vSphere and Microsoft Hyper-V environments for production workloads.

Understanding the differences in management, administration, and underlying architecture is important for the successful administration of both VMware vSphere and Microsoft Hyper-V. All of these differences affect data protection solutions and their interaction with the hypervisors. 

 

 Written by Alex Tray

Data breaches can immediately impact hundreds of millions or possibly billions of individuals in the data-driven world today. Data breaches have grown in scope along with digital transformation as attackers take advantage of our everyday reliance on data.  

Although it is impossible to predict how big cyberattacks may get in the future, this list of the biggest data breaches from the twenty-first century shows that they have already gotten ridiculously huge. 

Examples of data breaches and their impact 

Data breaches can be far more than a temporary terror. They may change the course of your life or your business. Businesses, governments, and individuals alike can experience huge complications from having sensitive information exposed. Whether you are offline or online, hackers can get to you through the internet, Bluetooth, text messages, or the online services that you use. 

Intentional attacks can occasionally be linked to the causes of data leaks. It may, however, also be the result of a person’s carelessness or weaknesses in the infrastructure of a business. 

Here is an example of a data breach: 

• An insider by accident. An illustration would be a worker viewing files on a coworker’s computer without the necessary authorization permissions. There is no information disclosed and the access is accidental. However, the data is regarded as compromised because it was read by an uninvited party. 
• Lost or stolen devices. An unencrypted and unlocked laptop or external hard drive — anything that contains sensitive information — goes missing. 
• Malicious outside criminals. “These are hackers who use various attack vectors to gather information from a network or an individual.”  

• A malicious insider: With the intention of hurting a person or business, this person willfully accesses and/or discloses data. “The malicious insider may have legitimate authorization to use the data, but the intent is to use the information in nefarious ways.” (“What is a Data Breach & How to Prevent One – Kaspersky”) 

 

Listen to the challenges of Data Analysis in cyber security

 

Most common types of data breaches in 21st century 

1. SQL Injection attack 

Similar to XSS assaults, a SQL Injection attack inserts malicious code into the system, but often SQL rather than HTML. In a SQL Injection attack, malicious code from the attacker accesses a system via a database.  

Although a lot of online apps employ databases as trustworthy third parties, it is crucial to make sure that no unauthorized parties are receiving data. Anyone with access to the database can steal information or carry out a SQL Injection attack to steal cash or other assets. 

2. Ransomware 

An unexpected notification informing you that your computer or phone has been compromised is known as ransomware. In this situation, the individual will inform you that if you pay a charge, they will provide it to you in exchange for keeping it private. This might range from being negligible to costing hundreds of thousands of dollars. 

In order to prevent the leak or deletion of crucial or compromising materials, many businesses work with risk management solution providers. 

3. XSS attack 

Web applications that exploit common vulnerabilities like XSS vulnerabilities may be exposed to cross-site scripting (XSS) attacks, a remote code execution (RCE) issue. When a remote attacker transmits malicious code to a web application, RCE problems can develop. 

Because the malicious code switches the web app’s execution to a script that could be anywhere on a computer network or even on other computers in the network, XSS vulnerabilities are usually simple to identify. 

4. MITM assault 

A man-in-the-middle (MITM) attack occurs when a perpetrator intercepts and steals data from a computer or network while posing as a third party. An attacker could, for instance, be present at a workplace, a hotel room, or a storage location when data is being seen by a computer user.  

The most frequent risk of MITM attacks is the public disclosure of sensitive data such as names, email addresses, dates of birth, financial information, health information, and other data. 

5. Digital breach 

A system or network environment where cardholder data is processed, stored, or sent is subject to an electronic breach if someone gains unauthorized access to it or deliberately attacks it. 

This could happen because of application-level assaults finding a system’s weaknesses via web servers or webpages. 

For instance, the healthcare sector is frequently impacted by data breaches since access to these networks exposes a lot of confidential patient credit card information. 

Major data breaches across the world

Some of the major data breaches that took place across the world 

Recently, major corporations have suffered data loss due to hacking and incidents of data breaches. Some of the most renowned of these are: 

1. Canva:

The namesake graphic design service, Canva, a Sydney-based business, was breached 2019, according to ZDNet. According to the hacker who alerted ZDNet, the incident resulted in the theft of data for almost 139 million customers. The compromise was caused by a hacker using the alias GnosticPlayers online. The hacker is well-known. He/she/they have been selling the 932 million user records that they acquired from 44 international businesses since 2019 February on the dark web. 

2. Shanghai National Police (SHGA):

The Shanghai National Police (SHGA) database was infiltrated in 2022. Major crucial data and information about billions of Chinese residents are contained in this database. The lot was being sold by HackerDan for 10 Bitcoin. 

3. Facebook:

Several online vulnerable databases were found to include 419 million records of Facebook users, dealing a fatal blow to over 20% of Facebook’s 2.3 billion users, according to TechCrunch. The records were kept on a server and were not password-protected, so anyone with an internet service could freely retrieve them. 

4. Microsoft:

250 million Microsoft customer records from 14 years ago have been exposed online without data encryption, according to a recent investigation. Recently, Microsoft has primarily been featured for different purposes in the headlines. Despite being frequently exploited, Microsoft has not released a patch for the Internet Explorer zero-day vulnerability. 

5. LinkedIn:

In June 2021, the dark web forum hosting 700 million LinkedIn users’ data was leaked, affecting more than 90% of the company’s user base. By abusing the site’s API, a hacker going by the handle “God User” used data scraping techniques before leaking the first private set of data of approximately 500 million users. 

Protect yourself from data breaches 

You must take the necessary steps to protect data and your confidential documents and electronic media in order to safeguard yourself from becoming a victim of a data breach, whether the perpetrator is a dumpster-diving identity thief looking for your discarded medical bills or a hacker who is targeting the network of your business in order to steal customer information. 

 

References: 

What is a Data Breach & How to Prevent One – Kaspersky 

50 self-explanatory data science quotes by thought leaders you need to read if you’re a Data Scientist, – covering the four core components of data science landscape. 

Data science for anyone can seem scary. This made me think of developing a simpler approach to it. To reinforce a complicated idea, quotes can do wonders. Also, they are a sneak peek into the window of the author’s experience. With precise phrasing with chosen words, it reinstates a concept in your mind and offers a second thought to your beliefs and understandings.  

In this article, we jot down 51 best quotes on data science that were once shared by experts. So, before you let the fear of data science get to you, browse through the wise words of industry experts divided into four major components to get inspired. 

 

 

Data strategy 

If you successfully devise a data strategy with the information available, then it will help you to debug a business problem. It builds a connection to the data you gather and the goals you aim to achieve with it. Here are five inspiring and famous data strategy quotes by Bernard Marr from his book, “Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things” 

1. “Those companies that view data as a strategic asset are the ones that will survive and thrive.” 
2. “Doesn’t matter how much data you have, it’s whether you use it successfully that counts.” 
3. “If every business, regardless of size, is now a data business, every business, therefore, needs a robust data strategy.” 
4. “They need to develop a smart strategy that focuses on the data they really need to achieve their goals.” 
5. “Data has become one of the most important business assets, and a company without a data strategy is unlikely to get the most out of their data resources.” 

Other Best Quotes on Data Science

Some other influential data strategy quotes are as follows: 

6. “Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.” – Chris Lynch, Former CEO, Vertica  

7. “You can’t run a business today without data. But you also can’t let the numbers drive the car. No matter how big your company is or how far along you are, there’s an art to company-building that won’t fit in any spreadsheet.” Chris Savage, CEO, Wistia 

8. “Data science is a combination of three things: quantitative analysis (for the rigor required to understand your data), programming (to process your data and act on your insights), and narrative (to help people comprehend what the data means).” — Darshan Somashekar, Co-founder, at Unwind media 

9. “In the next two to three years, consumer data will be the most important differentiator. Whoever is able to unlock the reams of data and strategically use it will win.” — Eric McGee, VP Data and Analytics 

10. “Data science isn’t about the quantity of data but rather the quality.” — Joo Ann Lee, Data Scientist, Witmer Group 

11. “If someone reports close to a 100% accuracy, they are either lying to you, made a mistake, forecasting the future with the future, predicting something with the same thing, or rigged the problem.” — Matthew Schneider, Former United States Attorney 

12. “Executive management is more likely to invest in data initiatives when they understand the ‘why.’” — Della Shea, Vice President of Privacy and Data Governance, Symcor

13. “If you want people to make the right decisions with data, you have to get in their head in a way they understand.” — Miro Kazakoff, Senior Lecturer, MIT Sloan 

14. “Everyone has the right to use company data to grow the business. Everyone has the responsibility to safeguard the data and protect the business.” — Travis James Fell, CSPO, CDMP, – Product Manager 

15. “For predictive analytics, we need an infrastructure that’s much more responsive to human-scale interactivity. The more real-time and granular we can get, the more responsive, and more competitive, we can be.”  Peter Levine, VC and General Partner ,Andreessen Horowitz 

Data engineering 

Without a sophisticated system or technology to access, organize, and use the data, data science is no less than a bird without wings. Data engineering builds data pipelines and endpoints to utilize the flow of data. Check out these top quotes on data engineering by thought leaders: 

16. “Defining success with metrics that were further downstream was more effective.” John Egan, Head of Growth Engineer, Pinterest 

17. ” Wrangling data is like interrogating a prisoner. Just because you wrangled a confession doesn’t mean you wrangled the answer.” — Brad Schneider – Politician 

18. “If you have your engineering team agree to measure the output of features quarter over quarter, you will get more features built. It’s just a fact.” Jason Lemkin, Founder, SaaStr Fund 

19. “Data isn’t useful without the product context. Conversely, having only product context is not very useful without objective metrics…” Jonathan Hsu, CFO, and COO,  AppNexus & Head of Data Science, at Social Capital 

20.  “I think you can have a ridiculously enormous and complex data set, but if you have the right tools and methodology, then it’s not a problem.” Aaron Koblin, Entrepreneur in Data and Digital Technologies 

21. “Many people think of data science as a job, but it’s more accurate to think of it as a way of thinking, a means of extracting insights through the scientific method.” — Thilo Huellmann, Co-fFounder, at Levity 

22. “You want everyone to be able to look at the data and make sense out of it. It should be a value everyone has at your company, especially people interacting directly with customers. There shouldn’t be any silos where engineers translate the data before handing it over to sales or customer service. That wastes precious time.” Ben Porterfield, Founder and VP of Engineering, at Looker 

23. “Of course, hard numbers tell an important story; user stats and sales numbers will always be key metrics. But every day, your users are sharing a huge amount of qualitative data, too — and a lot of companies either don’t know how or forget to act on it.” Stewart Butterfield, CEO,   Slack

 

 

Data analysis and models 

Every business is bombarded with a plethora of data every day. When you get tons of data, analyze it and make impactful decisions. Data analysis uses statistical and logical techniques to model the use of data:.  

24. “In most cases, you can’t build high-quality predictive models with just internal data.” — Asif Syed, Vice President of Data Strategy, Hartford Steam Boiler 

25. “Since most of the world’s data is unstructured, an ability to analyze and act on it presents a big opportunity.” — Michael Shulman, Head of Machine Learning, Kensho 

26. “It’s easy to lie with statistics. It’s hard to tell the truth without statistics.” — Andrejs Dunkels, Mathematician, and Writer 

27. “Information is the oil of the 21st century, and analytics is the combustion engine.” Peter Sondergaard, Senior Vice President, Gartner Research 

28. “Use analytics to make decisions. I always thought you needed a clear answer before you made a decision and the thing that he taught me was [that] you’ve got to use analytics directionally…and never worry whether they are 100% sure. Just try to get them to point you in the right direction.” Mitch Lowe, Co-founder of Netflix 

29. “Your metrics influence each other. You need to monitor how. Don’t just measure which clicks generate orders. Back it up and break it down. Follow users from their very first point of contact with you to their behavior on your site and the actual transaction. You have to make the linkage all the way through.” Lloyd Tabb, Founder, Looker 

30. “Don’t let shallow analysis of data that happens to be cheap/easy/fast to collect nudge you off-course in your entrepreneurial pursuits.” Andrew Chen, Partner at Andreessen Horowitz,  

31. “Our real job with data is to better understand these very human stories, so we can better serve these people. Every goal your business has is directly tied to your success in understanding and serving people.” — Daniel Burstein, Senior Director, Content & Marketing, Marketing Sherpa 

32. “A data scientist combines hacking, statistics, and machine learning to collect, scrub, examine, model, and understand data. Data scientists are not only skilled at working with data, but they also value data as a premium product.” — Erwin Caniba, Founder and Owner,Digitacular Marketing Solutions 

33. “It has therefore become a strategic priority for visionary business leaders to unlock data and integrate it with cloud-based BI and analytic tools.” — Gil Peleg, Founder , Model 9 – Crunchbase 

34.  “The role of data analytics in an organization is to provide a greater level of specificity to discussion.” — Jeff Zeanah, Analytics Consultant  

35. “Data is the nutrition of artificial intelligence. When an AI eats junk food, it’s not going to perform very well.” — Matthew Emerick, Data Quality Analyst 

36. “Analytics software is uniquely leveraged. Most software can optimize existing processes, but analytics (done right) should generate insights that bring to life whole new initiatives. It should change what you do, not just how you do it.”  Matin Movassate, Founder, Heap Analytics 

37. “No major multinational organization can ever expect to clean up all of its data – it’s a never-ending journey. Instead, knowing which data sources feed your BI apps, and the accuracy of data coming from each source, is critical.” — Mike Dragan, COO, – Oveit 

38. “All analytics models do well at what they are biased to look for.” — Matthew Schneider, Strategic Adviser 

39. “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” Geoffrey Moore, Author and Consultant 

Data visualization and operationalization 

When you plan to take action with your data, you visualize it on a very large canvas. For an actionable insight, you must squeeze the meaning out of all the analysis performed on that data, this is data visualization. Some  data visualization quotes that might interest you are: 

40. “Companies have tons and tons of data, but [success] isn’t about data collection, it’s about data management and insight.” — Prashanth Southekal, Business Analytics Author 

41. “Without clean data, or clean enough data, your data science is worthless.” — Michael Stonebraker, Adjunct Professor, MIT 

42. “The skill of data storytelling is removing the noise and focusing people’s attention on the key insights.” — Brent Dykes, Author, “Effective Data Storytelling” 

43. “In a world of more data, the companies with more data-literate people are the ones that are going to win.” — Miro Kazakoff, Senior Lecturer, MIT Sloan 

44. The goal is to turn data into information and information into insight. Carly Fiorina, Former CEO, Hewlett Packard 

45. “Data reveals impact, and with data, you can bring more science to your decisions.” Matt Trifiro, CMO, at Vapor IO 

46. “The skill of data storytelling is removing the noise and focusing people’s attention on the key insights.” — Brent Dykes, data strategy consultant and author, “Effective Data Storytelling” 

47. “In a world of more data, the companies with more data-literate people are the ones that are going to win.” — Miro Kazakoff, Senior Lecturer, MIT Sloan 

48. “One cannot create a mosaic without the hard small marble bits known as ‘facts’ or ‘data’; what matters, however, is not so much the individual bits as the sequential patterns into which you organize them, then break them up and reorganize them'” — Timothy Robinson, Physician Scientist 

49. “Data are just summaries of thousands of stories–tell a few of those stories to help make the data meaningful.” Chip and Dan Heath, Authors of Made to Stick and Switch

Parting thoughts on amazing data science quotes

Each quote by industry experts or experienced professionals provides us with insights to better understand the subject. Here are the final quotes for both aspiring and existing data scientists: 

50. “The self-taught, un-credentialed, data-passionate people—will come to play a significant role in many organizations’ data science initiatives.” – Neil Raden, Founder, and Principal Analyst, Hired Brains Research. 

51. “Data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.” – Mike Loukides, Editor, O’Reilly Media. 

Have we missed any of your favorite quotes on data? Or do you have any thoughts on the data quotes shared above? Let us know in the comments.

As data scientists, our job is not to run the whole security operation in our organizations to avoid a security breach. However, as we work very closely with data, we must understand the importance of having good, robust mechanisms in place to prevent sensitive and personally identifiable information from getting into the wrong hands, or from any cyber attack. Hence, the need for data security.

Strong passwords? Not enough

Setting ourselves up with a strong password might not cut it in today’s world. Some of the world’s biggest banks, which have an army of highly skilled security professionals, have suffered ever-more smarter cyber attacks. Today, users are logging into work systems and databases through biometrics such as fingerprint scanning technology on smartphones, laptops, and other devices or computers.

Two-factor authentication is also a popular mechanism of data security, which goes beyond simply identifying and authenticating a user through their password alone. Users are now logging into systems using a one-time password – which is sent to their work email, requiring another form of login – in combination with their fingerprint password. Generating a random number or token string each time a user logs into a system can reduce the risk of a single password being decrypted or obtained some other way.

Finishing the equation

User identity and authentication are only half of the equation, however. The other half is using anomaly detection algorithms or machine learning to pick up on unusual user activity and behavior once a user has logged on. This is something we as data scientists can bring to the table in helping our organizations better secure our customer or business data. Some of the key features of anomaly detection models include the time of access, location of access, type of activity or use of the data, device type, and how frequently a user accesses the database.

The model collects these data security points every time a user logs into the database and continuously monitors and calculates a risk score based on these data security points and how much they deviate from the user’s past logins. If the user reaches a high enough score, an automated mobile alert can be sent to the security team to further investigate or to take action.

Data security examples

Some obvious data security examples include a user who lives in Boston who logged out of the database 10 minutes ago but is now accessing the database in Berlin. Or, a user who usually logs in to the database during work hours is now logging in at 3 am.

Other examples include an executive assistant, who rarely logs into the database, and is now frequently logging into the database every 10 minutes. A data scientist, who usually aggregates thousands of rows of data is now retrieving a single row.

A marketer, who usually searches the database for contact numbers, is now attempting to access credit card information, even though that marketer already knows she/he does not have access to this information.

Another way data scientists can safeguard their customer or business data is to keep the data inside the database rather than exporting a subset or local copy of the data onto their computer or device. Nowadays, there are many tools to connect different database providers to R or Python, such as the odbcConnect() function as part of the RODBC library in R, which reads and queries data from a database using an ID and password rather than importing data from a local computer.

The ID and password can be removed from the R or Python file once the user has finished working with the data, so an attacker cannot run the script to get the data without a login. Also, if an attacker were to crack open a user’s laptop, he or she would not find a local copy of the data on that device.

Row and column access is another example of data security through fine-grained access controls. This mechanism masks certain columns or rows for different users. These masked columns or rows in tabled data usually contain sensitive or personally identifiable information. For example, the columns which contain financial information might be masked by the data science team but not by the finance/payments processing team.

Conclusion & other tips

Other ways to safely deal with sensitive and personally identifiable information include differential privacy and k-anonymity. To learn about these techniques, please read Dealing with data privacy – anonymization techniques.

 

Written by Rebecca Merrett

Learn how to configure the security of your Windows 10 account and be the true owner of your personal data and your privacy.

Technology is something wonderful that for centuries has been improving people’s lives and facilitating day-to-day, allowing us to do things that until now were impossible. It is undeniable how the internet has changed our lives and connected us with people from all over the globe, but it also has its drawbacks.

The latest advances in technology have reduced our privacy to a level that we had never before reached. It is no longer necessary to be a famous star so that our privacy is worth a lot of money. Many of the services and tools we use every day are collecting our personal data without us being aware, in exchange for making our lives easier.

Whether to protect you from hackers who want to steal your banking information or because you do not feel comfortable sharing your location with all the applications you use, you must be aware of how to protect yourself from these dangers.

Here I propose a few essential steps in Windows 10 to be the owner of your data and know who wants to know where you are or what pages you visit, and even, avoid being spied on through your computer’s camera.

1. Say no to the fast installation of Windows 10

When it comes to Windows 10 or an application, many times we look for the fastest option in which we have to do as little as possible and companies increasingly offer more options for users to get rid of these very tedious processes.

The downside is that the more we disengage from the configuration and installation process, the more power we give companies to do what they want with our privacy, you know the saying, “if you want something to be done well, you have to do it yourself”.

When installing Windows 10 make sure you choose the custom configuration to monitor each of the permissions you give the system. Then go to the privacy settings. To get to this section, you only have to press the Windows key and the ‘I’ key at the same time. There you can configure the Windows 10 privacy to your liking, although you will not be able to access the configuration of the other applications. You will have to go one by one. Even if you are configuring your Windows Office, you can click here to read about how to do it properly.

2. Cut the wings to Cortana

Virtual assistants are very useful to make our lives easier but to know each other so well as to be really useful we must give them access to a whole range of personal data. If you work with your computer, you may not be interested in Cortana having access to your company’s data or bank details. Although in the end you do not care and let them work with this information, at least we recommend that you take a look at everything Cortana wants to know about you.

In the configuration section of Cortana, you can delete all the data that this assistant has from you or select those in particular that seem too private.

3. Turn off your location

As mobile phones do, Windows 10 automatically tracks your location at any time and saves this information for about 24 hours to also share it with any third-party application that you have downloaded.

Once again in the privacy settings section, you can deactivate the tracking of your location, or activate it in case you need it in a timely manner. In addition, it is recommended that you review the configuration of each of the applications that you install on your computer and be aware of which ones are trying to know where you are.

4. Block ad tracking

Whether you are browsing the different online stores looking for a new smartphone or you are simply checking hotels to find out how much it would cost you to go on a weekend trip, you will see hundreds of ads about things you have been looking for.

That’s ad tracking and it’s a nuisance, but the good thing is that it can be blocked. Obviously, by default Windows 10 has it activated because it is great for companies to know what you are thinking of spending your money on.

In the privacy settings, you will find a section where you can deactivate the option “Allow applications to use my advertising ID”.

5. Don’t allow access to your camera

How many times has Hollywood warned us with their films and TV series about hackers that are dedicated to controlling the cameras of other people’s laptops to spy on a girl and how many times we would have thought it was an invention of the screenwriters?

Well it is a very real possibility and experts warn of how easy it is to do this, so, it is more than recommended to block the camera and only activate it when you have to use it for a conference or a family video call. Moreover, you cannot only disable the camera from the computer configuration, but you can cover it with small protectors that give a lot of peace and do not cost a lot.

6. Disable access to the microphone

If we block the camera, how can we not block the microphone? It is true that if you want to give instructions to Cortana you need it, but if you have decided to silence her completely, you should also do the same with the microphone.

7. Who can see your account information?

Another data point we give to Windows and it shares with others is the account data, such as name and email address. If we go to the section “Account information” we will see that many of the applications we use have access to this data.

Customizing this section of the configuration never hurts and shares as little data as possible with applications.

8. Eliminate tracking of the timeline

This point is related to point number four. Surfing the internet should imply that others know what you are looking for even if they are completely harmless pages. Tracking the timeline involves tracking all the websites you have visited, eliminating it increases your privacy, and control of your data. The bad thing is that you have to do it on a regular basis, like the browser history, which the experts recommend to delete it in the usual way.

9. Check the privacy settings after each update

We are sorry to inform you that after a system update it is possible that many of the steps you have taken today will be lost and you will have to fix them where you left them. Microsoft usually re-establishes all the privacy settings and reinforces them by default when restarting. Many complaints have been made about this aspect but it has fallen on deaf ears. Nothing happens but this should not prevent us from being attentive. To stay alert, it is best to turn off automatic updates and be aware of when an important one arrives.

This does not mean it’s better not to update. Updates are important to get new interesting features and improvements in system security but we should not give them up unless we see that they return to give problems.

10. Do not leave your privacy in the hands of others

This advice serves both Windows 10 users and any other system and device users, even Apple. User data is becoming the great business of the 21st century. Our privacy, tastes, interests, and other personal data are worth a lot to companies but they should be worth more to ourselves and we should protect them as if they were gold.

It requires a little effort to be aware of tricks like these and steps or tools that help us keep our privacy as intact as possible.

Review the relationship between data science and cybersecurity with the most common use cases.

Data science brings a logical structure to unstructured data. Data scientists use machine or deep learning algorithms to compare normal and abnormal patterns. In cybersecurity, data science helps security teams distinguish between potentially malicious network traffic and safe traffic.

Applications of data science in cybersecurity are relatively new. Many companies are still using traditional measures like legacy, antiviruses, and firewalls. This article reviews the relationship between data science and cybersecurity and the most common use cases.

How data science changed cyber security

Large organizations have a lot of data moving throughout their network. The data can originate from internal computers, IT systems, and security tools. However, these endpoints do not communicate with each other. The security technology responsible for detecting attacks cannot always see the overall picture of threats.

Before the adoption of data science, most large organizations used the Fear, Uncertainty, and Doubt (FUD) approach in cybersecurity. The information security strategy was based on FUD-based assumptions. Assumptions about where and how attackers may attack.

With the help of data science, security teams can translate technical risk into business risk with data-driven tools and methods. Ultimately, data science enabled the cyber-security industry to move from assumptions to facts.

The relationship between data science and cybersecurity

The goal of cybersecurity is to stop intrusions and attacks, identify threats like malware, and prevent fraud. Data science uses Machine Learning (ML) to identify and prevent these threats.

For instance, security teams can analyze data from a wide range of samples to identify security threats. The purpose of this analysis is to reduce false positives while identifying intrusions and attacks.

Security technologies like User and Entity Behavior Analytics (UEBA) use data science techniques to identify anomalies in user behavior that may be caused by an attacker. Usually, there is a correlation between abnormal user behavior and security attacks.

These techniques can paint a bigger picture of what is going on by connecting the dots between these abnormalities. The security team can then take proper preventative measures to stop the intrusion.

The process is the same for preventing fraud. Security teams detect abnormalities in credit card purchases by using statistical data analysis. The analyzed information is then used to identify and prevent fraudulent activity.

Data science has had a profound effect on cybersecurity.  As it is important to learn data science to stay competitive in every industry, similarly, in this section we will explain the key impacts of data science in the field of cybersecurity.

Intrusion, Detection, and Prediction

Security professionals and hackers always played a game of cat-and-mouse. Attackers used to constantly improve their intrusion methods and tools. Whereas security teams improved detection systems based on known attacks. Attackers always had the upper hand in this situation.

Data science techniques use both historical and current information to predict future attacks. In addition, machine learning algorithms can improve an organization’s security strategy by spotting vulnerabilities in the information security environment.

Establishing DevSecOps cycles

DevOps pipelines ensure a constant feedback loop by maintaining a culture of collaboration. DevSecOps adds a security element to DevOps teams. A DevSecOps professional will first identify the most critical security challenge and then establish a workflow based on that.

Data scientists are already familiar with DevOps practices because they use automation in their workflows. As a result, DevSecOps can easily be applied to data science in a process called DataSecOps. This type of agile methodology enables data scientists to promote security and privacy continuously.

Behavioral analytics

Traditional antiviruses and firewalls match signatures from previous attacks to detect intrusions. Attackers can easily evade legacy technologies by using new types of attacks.

Behavior analytics tools like User and Entity Behavior Analytics (UEBA) use machine learning to detect anomalies and potential cyberattacks. If, for example, a hacker stole your password and username, they may be able to log into your system. However, it would be much harder to mimic your behavior.

Data protection with associate Rule Learning

Associate Rule Learning (ARL) is a machine learning method for discovering relations between items in large databases. The most typical example is market-based analysis. ARL shows relations between items that people buy most frequently. For example, a combination of onions and meat may relate to a burger.

ARL techniques may also recommend data protection measures. The ARL studies the characteristics of existing data and alerts automatically when it detects unusual characteristics. The system constantly updates itself to detect even the slightest deviations in the data.

Backup and data recovery

New backup technologies are leveraging machine learning to automate repetitive backup and recovery tasks. Machine learning algorithms are trained to follow the priorities and requirements of security plans.

Backup and recovery systems based on ML can help incident response teams organize workspaces and resources. For example, ML tools can access and recommend the necessary equipment and locations for a particular business recovery plan based on the company’s needs.

Conclusion

Cyber attacks are always evolving, and no one knows what form they will take in the future. Data science enables companies to predict possible future threats based on historical data with technologies like UEBA. Intrusion Detection Systems (IDS) use regression models to predict potential malicious attacks. Data science can leverage the power of data to create stronger protection against cyber attacks, and data losses.

 

 

Written by Gilad Maayan