Insider threats are becoming increasingly challenging to detect, as employees and contractors may misuse their legitimate access to bypass security measures. Behavioral analytics offers a powerful tool for identifying subtle activity changes that could indicate malicious actions or unintentional risks before they evolve into serious breaches.

This session will dive into advanced methods for applying behavioral analytics to insider threat detection, including leveraging machine learning, anomaly detection algorithms and seamless integration with existing security tools.

The session will also cover:

• How to train models that pinpoint deviations in user activity across diverse systems;
• Implementing anomaly detection techniques to identify irregularities as they occur;
• Using behavioral data to enhance automation and incident response workflows.