After a successful security breach, complex cyber-attacks can imitate normal behavior while preparing for the active stage of the attack. It is here, where the Anomaly Behavior Analysis helps, combining real-time threat detection, network visualization, and advanced investigation capabilities in a single unified system. Using proprietary machine learning and artificial intelligence algorithms, it works by passively analyzing raw network traffic to form an evolving understanding of ‘normal’ for every user, device, and subnet in an organization. Without presuming to know in advance what activity is ‘malicious’ or not, it independently learns to detect significant deviations, and immediately alerts the organization to emerging threats.
