Boosting IT Security with AI-driven SIEM

Boosting IT Security with AI-driven SIEM

AI and ML are essential in cybersecurity. AI is great at distinguishing between normal and abnormal behaviour. By implementing ML, computer systems can be programmed and trained to improve their ability to detect strange security anomalies and deviant behaviour. Using these techniques in cybersecurity dramatically improves the accuracy of threat hardening. In addition, ML models can perform preliminary investigations of detected threats and significantly reduce false positives in security systems.

We have used our intelligence to solve problems and secure our current lifestyle. Why not use artificial intelligence to increase that possibility? The versatility of AI enables multiple applications. Why not use integrated AI and SIEM solutions to increase the efficiency of your data analytics, vulnerability, and threat management software?

Integrating AI and SIEM are becoming increasingly popular among software developers to attack next-generation threats with next-generation solutions. Learn how AI and SIEM solutions can improve the efficiency of your IT security team.

Security information and event management (SIEM) solutions monitor network activity. They use threat intelligence and user and entity behavioural analytics (UEBA) to detect and mitigate attacks, ensuring that all incidents occurring in your IT infrastructure are covered. Provides a complete scenario of the activity.

AI and SIEM: Is This Integration Systematic?

AI and SIEM solutions enable IT and security teams to be more efficient by detecting vulnerabilities, threats, and cyberattacks. The technology is enhanced to predict attacks from unknown threats with minimal human analyst intervention.

The combination of AI and SIEM helps IT security teams reduce the frequency of false positives that require human intervention. This allows SIEM analysts to redirect time spent verifying positive results to higher priority activities.

Integrating AI with your SIEM solution provides the following Benefits:

Collect, process, and analyze large amounts of data without slowing down the system's responsiveness.

AI optimizes the UEBA (User and Entity Behavioral Analytics) engine to detect irregular patterns in user behaviour. These patterns include changes in users' regular system access schedules and connections from different geographical points.

Evolve from traditional reactive security systems to new proactive solutions. This is made possible thanks to high-quality performance guided by machine learning techniques.

Reducing false positives allows IT and security groups to focus their intuition and creativity on high-priority events.

Join our webinar and learn more visit: https://ltssecure.com/ai-and-ml-based-siem/