2018 article

Case Study III: CFC-Based Byzantine Attack Detection

ADVERSARY DETECTION FOR COGNITIVE RADIO NETWORKS, pp. 63–72.

By: X. He*, H. Dai n , X. He & H. Dai

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
Source: Web Of Science
Added: October 16, 2018

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.