Distributed Detection of Replica Cluster Attacks in Sensor Networks Using Sequential Analysis

Due to the unattended nature of wireless sensor networks, an adversary can capture and compromise sensor nodes, generate replicas of those compromised nodes, and mount a variety of attacks with the replicas he injects into the network. This is a severe type of attack in the sense that the attacker can leverage the compromise of a single node to create widespread effects on the network. In particular, we are interested in replica cluster attacks, in which many replicas with the same identity form a cluster in a small region. This is also a dangerous attack because attacker can leverage a replica cluster to harmfully impact on the much of the network. To defend against replica cluster attacks, we propose an efficient and effective replica cluster detection scheme using the sequential probability ratio test. We show analytically that our scheme achieves a high replica cluster detection capability.