2018 article
Case Study III: CFC-Based Byzantine Attack Detection
ADVERSARY DETECTION FOR COGNITIVE RADIO NETWORKS, pp. 63β72.
The multi-HMM inference algorithm presented in the previous chapter can effectively assist the Byzantine attack detection when either the percentage of the malicious SUs or their flipping probability is not too high. To further enhance the detection performance, a tailor-designed Byzantine attack detection scheme, termed CFC, will be presented in this chapter. In this method, two natural yet effective CFC statistics that can capture the second-order properties of the underlying spectrum dynamics and the SUs spectrum sensing behaviors are constructed for Byzantine attacker identification. More specifically, we will first briefly clarify the underlying system model and then presents the CFC based Byzantine attack detection algorithm. In addition, performance analysis of this method will also be presented.