Context-Awareness to improve Anomaly Detection in Dynamic Service Oriented Architectures

Research Area: Uncategorized Year: 2016
Type of Publication: In Proceedings Keywords: Anomaly Detection, Monitoring, Service Oriented Architecture, SOA, Context Aware, Multi Layer
Authors: Tommaso Zoppi; Andrea Ceccarelli; Andrea Bondavalli
Editor: Amund Skavhaug; Jérémie Guiochet; Friedemann Bitsch
Book title: Computer Safety, Reliability and Security (SAFECOMP 2016)
Series: 9922 Pages: 145-158
ISBN: 978-3-319-45477-1
Revealing anomalies to support error detection in softwareintensive systems is a promising approach when traditional detection mechanisms are considered inadequate or not applicable. The core of anomaly detection lies in the definition of the expected behavior of the observed system. Unfortunately, the behavior of complex and dynamic systems is particularly difficult to understand. To improve the accuracy of anomaly detection in such systems, in this paper we present a contextaware anomaly detection framework which acquires information on the running services to calibrate the anomaly detection. To cope with system dynamicity, our framework avoids instrumenting probes into the application layer of the observed system monitoring multiple underlying layers instead. Experimental evaluation shows that the detection accuracy is increased considerably through context-awareness and multiple layers monitoring. Results are compared to state-of-the-art anomaly detectors exercised in demanding more static contexts.
Full text: Paper_V16b.pdf

Resilient Computing Lab, 2011

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