Gossip-Based Outlier Detection for Mobile Ad Hoc Networks
Wenjia Li, University of Maryland, Baltimore County

It is well understood that Mobile Ad Hoc Networks (MANETs) are extremely susceptible to a variety of attacks. Many security schemes have been proposed that depend on identifying nodes that are exhibiting malicious behavior such as packet dropping, packet modification, and packet misrouting. We argue that in general, this problem can be viewed as an instance of detecting nodes whose behavior is an outlier when compared to others. In this work, we propose a gossip-based outlier detection algorithm for MANETs. The algorithm leads to a common outlier view amongst distributed nodes with a limited communication overhead. Simulation results demonstrate that the proposed algorithm is efficient and accurate.