Distributed Detection in Wireless Sensor Networks under Byzantine Attacks

Abstract

Distributed detection in wireless sensor networks (WSNs) under Byzantine attacks is studied in this paper. A new kind of Byzantine attacks, neighborhood malicious Byzantine attacks (NMBA), is proposed. In this type of Byzantine attacks, part of sensors is conquered and reprogrammed by an intelligent adversary. These sensors then are conducted to send false information to the fusion center (FC) in order to confuse it. We see that the attacking performance of NMBA is very close to that of collaborative malicious Byzantine attacks (CMBA) and outperforms independent malicious Byzantine attacks (IMBA). Decision fusion becomes impossible when attacking power which is the fraction of compromised sensors in WSNs exceeds a specific value. A closed-form expression for the value is derived. For mitigating attacking effect brought by NMBA, a strategy for estimating the attacking power is proposed. Furthermore, a scheme to identify Byzantine attackers is presented. Two kinds of discrepancy distance are constructed in this paper to help in identifying Byzantine attackers. We prove that most of Byzantine attackers are identified and performance of the identifying scheme is proved to be excellent. A data fusion scheme based on both dynamic threshold and the identifying scheme is analyzed in this paper. Numerical results are also provided to support the schemes and approaches.