Behavior-Profile Clustering for False Alert Reduction in Anomaly Detection Sensors

Anomaly Detection (AD) sensors compute behavior profiles to recognize malicious or anomalous activities. The behavior of a host is checked continuously by the AD sensor and an alert is raised when the behavior deviates from its behavior profile. Unfortunately, the majority of AD sensors suffer from high volumes of false alerts either maliciously crafted by the host or originating from insufficient training of the sensor. We present a cluster-based AD sensor that relies on clusters of behavior profiles to identify anomalous behavior. The behavior of a host raises an alert only when a group of host profiles with similar behavior (cluster of behavior profiles) detect the anomaly, rather than just relying on the host's own behavior profile to raise the alert (singleprofile AD sensor). A cluster-based AD sensor significantly decreases the volume of false alerts by providing a more robust model of normal behavior based on clusters of behavior profiles. Additionally, we introduce an arc...

• Type: Conference
• Year: 2008
• Where: ACSAC
• Authors: Vanessa Frías-Martínez, Salvatore J. Stolfo, Angelos D. Keromytis
• Keywords: ACSAC 2008, Ad Sensors, Behavior Profiles, Cluster-based Ad Sensors, Security Privacy