Performance evaluation of immunity-based statistical en-route filtering in wireless sensor networks

Abstract

Statistical en-route filtering (SEF) schemes can detect and eliminate false data injection attacks in wireless sensor networks. However, SEF does not address the identification of the compromised nodes which are injecting false reports. Therefore, we have proposed an immunity-based SEF to identify compromised nodes and achieve earlier detection of false reports. In the proposed scheme, each node has a list of neighborhood nodes and assigns credibility to each neighboring node. Each node can update the credibility of a neighboring node based on the success or failure of filtering and communication, and can then use the updated credibility as the probability of the next communication. In this article, some simulation results show that the immunity-based SEF outperforms the original SEF.