You're aiming to enhance Information Security. Which latest trends should you be focusing on?

As an AI enthusiast and security researcher, it's wise to be cautious with new, innovative methods. The cybersecurity market is vast and sometimes includes vendors promoting products without thorough research and validation. Begin by adopting security principles such as Zero Trust and secure by design. Choose proven strategies and technology stacks that prioritize robust security practices. While caution is important, don't disregard all new technologies. Consider AI or ML-powered options that have been vetted by third-party evaluations and shown to deliver concrete results. Avoid relying solely on internal testing claims or promotional content.

Agreed that AI is part of every infra component, but in the information security space there needs to be additional validations that are required to ensure that the actions by the AI are providing the right actions. Per my view, the monitoring of the AI actions also should be done for better understanding of the issues avoided or mitigated.

Sure, AI defense or anything with the word AI will sound helpful in some way, shape, or form today, but don't be so quick to jump on the bandwagon. Do your research, and take your time. Our job is to secure information. If there is a more effective way to do this than it should be done, if it means using AI then great! But the AI tool needs to be vetted!

This is a false start. AI is nowhere close to being ready for primetime, IMO. The DNNs don't have enough rows to set the weights and activations correctly. All vendors are selling aspirational vaporware right now, hoping you don't look too closely. My advice. Install plain-jane observability and write your own bridge in cybersecurity. Don't let an o11y vendor sell you cyber. Get two different solutions and custom-wire them together. Observability is an early warning system. It has zero intelligence but can easily find anything anomalous that is then passed to cyber for threat analysis. It's a beautiful combo!

Importance of (AI) & (ML) in cybersecurity is growing, as these technologies enable real-time threat analysis through data pattern recognition. Organizations using AI & ML can adopt more proactive security measures. As companies move to the cloud, Cloud Security Posture Management (CSPM) becomes crucial for securing cloud environments. CSPM tools help organizations monitor and remediate security policies, identify vulnerabilities.penalties.Thisnecessitates robust data governance frameworks and transparency in data handling, which can improve customer trust.The cybersecurity skills gap remains a significant challenge, placing stress on existing personnel. Organizations are encouraged to invest in training.

AI has become the most discussed topic now a days, Here are my 2 cents on AI defense. Adversarial Machine Learning: Understanding Vulnerabilities in AI: As AI systems become more prevalent, it's essential to study adversarial attacks that aim to deceive machine learning algorithms. Invest in research to improve the robustness of AI algorithms against these types of attacks, implementing methods such as adversarial training. AI for Automated Compliance: Regulatory Compliance Monitoring: Leverage AI to automate monitoring and reporting for regulatory compliance requirements such as GDPR, HIPAA, or PCI DSS. This ensures that security measures evolve in line with compliance mandates.

There is always a innovation, technology in market. I still believe AI in Information Security has lot to cover. The traditional approach like Zero Trust are still the best in market & there others also. Still you can use AI Solutions with help of Establish Third Vendor for data security.

Implement identity and access management, micro-segmentation, and continuous monitoring to limit the potential damage of breaches. Implement AI-driven security solutions for predictive analytics, anomaly detection, and automated responses to threats. Utilize tools that can collect and correlate data from different sources to improve threat detection. Implement robust cloud security measures to protect data and applications. Deploy vulnerability management solutions to reduce response times and improve security posture. Stay updated with regulatory changes, implement data protection policies, and ensure transparency in data handling practices.

Just because you sit on a cloud does not mean you can transfer all responsibility to them. It is still your information. You have just as much responsibility. Ask your cloud provider hard questions. How are they securing your data? How often are they backing it up? Who can see your data? etc....

Every week a new cyberattack appears in the headlines, bringing yet another business to a screeching halt. As CEOs are focused on capitalizing on the post-COVID economic surge, it is critical that they do not ignore the risk of a ransomware attack and its ability to instantly bring their business to its knees. Research shows that 51% of small and midsize businesses still lack a current cyber strategy, leaving their business – and the golden opportunity of recovery – at risk. Get professional help. It may seem expense until your system gets hacked and the ransom is $100,000 to get your data back.

Security incidents are always topic of the day. Here ismy perspective on the Cloud Security. Cloud-Native Security Solutions: Utilization of CASB: Implement a Cloud Access Security Broker (CASB) to gain visibility and control over data in the cloud, ensuring proper usage of cloud resources and enforcing security policies. Serverless Security: Securing Function-as-a-Service (FaaS): As organizations adopt serverless architectures, focus on the unique security challenges they introduce. Implement security monitoring that specifically addresses the functions and APIs in serverless environments to ensure proper access controls and audit logs.

You cannot completely abolish risk, Can manage it. Sometime moving to third vendor such as cloud. It is very important to identify required cloud technology & vendor. Sign the NDA, Do the Market Search. Search on Cloud Security Solution.

Zero Trust helps organizations meet regulatory requirements by ensuring that sensitive data is protected and access is controlled.

Behavioral Analytics: Contextual Risk Assessment: Implement user and entity behavior analytics (UEBA) to scrutinize user behaviors and flag anomalies that may indicate compromised credentials or insider threats. Contextual awareness should inform access decisions rather than relying solely on static policies. Continuous Validation: Dynamic Access Controls: Move toward a continuously verifying access model that not only checks user credentials at login but also periodically reassesses the legitimacy of access based on real-time factors such as changes in user behavior, device health, and geographical location.

The best thing about ZT technology is to trust no one and verify everything. This approach has very low or minimal impact on Data.

Threat Intelligence Platforms: Building a Centralized Repository: Create or invest in a threat intelligence platform (TIP) to aggregate multiple threat feeds and correlate intelligence. This allows for more informed decision-making and facilitates better sharing of relevant threat data across teams. Cyber Deception Techniques: Deploy Decoy Systems: Use honeypots and deception technologies to attract and analyze malicious behavior. This can provide invaluable intelligence on attacker methods, techniques, and tools, while also diverting threats away from critical assets.

SIEM always has play good role in Identify Threat in infrastructure, Now SOAR is 1 step had with playbook configured will give more in-depth analysis & control over thread vector, both inside & outside.

Differential Privacy: Implement differential privacy techniques to analyze data without compromising individual privacy. This can be particularly useful when sharing insights derived from user data without revealing personal information. Privacy-Aware AI: Ensure that AI systems are built with privacy considerations from the ground up. Use frameworks and tools that incorporate privacy by design, meaning privacy risks are identified and mitigated during the development phase.

Prioritizing a Secure Software Development Life Cycle (SDLC) is essential for any security program because it integrates security at every phase of development, from initial design through deployment and maintenance. By embedding security practices early, developers can identify and mitigate vulnerabilities before they evolve into costly issues, ensuring the software is robust and resilient against threats. This proactive approach not only reduces the likelihood of security breaches but also streamlines the management of security foundations post-deployment, as potential risks are addressed systematically rather than reactively. A Secure SDLC fosters a culture of security awareness among development teams, promoting continuous improvement.