Artificial intelligence and machine learning are critical for a mature cybersecurity program. These technologies enable organizations to detect time, count, and pattern anomalies; and compute a risk score for every user and entity in the network. Instead of writing threat detection rules, security analysts can rely on the system learning on its own and alerting them about potential threats. AI and ML in cybersecurity helps decrease false positives, while increasing the occurrence of true positives.

Join us in this webinar to learn how AI and ML in cybersecurity have evolved, what they hold for us in the future, and the main elements of an ML-based SIEM solution.

Agenda:

• Understanding how AI and ML in cybersecurity began.
• Detecting time, count, and pattern anomalies.
• Scoring risks for proactive security.
• Analyzing peer groups and seasonal factors to improve risk scoring.
• Modeling anomalies for added flexibility, precision, and effectiveness.