Resilient against report fabrication attack in clusters of heterogeneous sensor networks

Abstract

A major threat in wireless sensor network is report fabrication attack. The existing approaches in which each forwarding sensor along a path probabilistically filters out injected false data may not be adequate because such protection may break down when more than a threshold number of nodes are compromised. As an alternative, we present a sink filtering scheme in clusters of heterogeneous sensor networks to solve the threshold breakdown problem. Besides basic sensors, we add some powerful data gathering sensors, termed as cluster heads (CHs). To be accepted by the sink, each aggregation report generated by a CH must carry multiple keyed message authentication codes (MACs); each MAC is generated by a basic sensor that senses the event. We analyze the resilience and overhead of the sink filtering scheme. Both analytical and simulation results show that the scheme is resilient to an increasing number of compromised nodes, with graceful performance degradation. The scheme is also scalable and efficient in communication, computation and storage