Anomaly Detection for Wireless Ad-Hoc Routing Protocols

Abstract

Mobile Ad-hoc networking (MANET) is an important emergingtechnology. As recent several security incidents remind us, noopen computer system is immune from intrusions. The routing protocolsin ad-hoc networks are key components yet vulnerable and presentspecial challenges to intrusion detection.

In this thesis, we propose an anomaly detection scheme for existingad-hoc routing protocols. Our approach relies on information from localrouting data and other reliable local sources. Our approach models thetemporal/sequential characteristics of observations and uses entropyanalysis for feature selection. Classification algorithms are used tocompute anomaly detection models. We present case studies on DSR andDSDV protocols using the ns-2 simulator. The overall results thusfar are very encouraging. We discuss how the available information from arouting protocol influences anomaly detection performance and attemptto provide guidelines on what features we need for anomaly detection.

Finally, we also discuss several challenging issues and propose ourfuture work.