Resilience of sink filtering scheme in wireless sensor networks

One of severe security threats in wireless sensor network is node compromise. A compromised node can easily inject false data reports on the events that do not occur. 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. To solve this problem, we present a sink filtering scheme in clusters of heterogeneous sensor networks. In addition to basic sensors, some powerful data gathering sensors termed as cluster heads (CHs) are added. 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. The sink node checks the validity of the carried MACs in an aggregation report and filters out the forged report. 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. Particularly, we adopt Poisson Approximation to investigate the performance tradeoff between resilience and overall cost, and give some suggestions on how to choose the parameters. The scheme is also scalable and efficient in communication, computation and storage.