A Multi-layer Anomaly Detector for Dynamic Service-Based Systems

Revealing anomalies to support error detection in complex systems is a promising approach when traditional detection mechanisms (e.g., based on event logs, probes and heartbeats) are considered inadequate or not applicable. The detection capability of such complex system can be enhanced observing different layers to achieve richer information that describes the system status. Relying on an algorithm for statistical anomaly detection, in this paper we present the definition and implementation of an anomaly detector able to monitor data acquired from multiple layers, namely the Operating system and the Application Server, of a remote physical or virtual node. As case study, such monitoring system is applied to a node of the Secure! crisis management servicebased system. Results show the monitor performance, the intrusiveness of the probes, and ultimately the improved detection capability achieved observing data from the different layers.