ML helps detect anomalies
Many security teams still rely on static signatures to detect threats. They either rely on an intrusion detection system (IDS) for network analysis or on static behavioral detections based on endpoint logs. But with more and more data, it becomes difficult to keep track and cover all sources and attack patterns with individual rules. To overcome these challenges, Exeon says machine learning (ML) algorithms help change the perspective of detection development. Anyone who uses ML can learn the normal state of communication, recognize deviations and...
