Detecting Primary Emulation Attacks Based on Energy Fingerprint Matching in Cognitive Radio Networks
基于能量指纹匹配的无线认知网络仿冒主用户攻击检测

Spectrum sensing is an essential mechanism in cognitive radio networks. While so many works have been done or being carried on upon improving the efficiency of the sensing process, there is no appropriate scheme to realize security sensing in untrustworthy environments. We proposed a mechanism based on Energy Fingerprint(EF) matching to address a typical attack in CR networks, the Primary User Emulation Attack(PUEA). Based on the distribution of their positions and through energy detection,the secondary users can create PU's EF which is used as an identification of node to analyze the spectrum accessing mode of different users, and finally detect the PUEA. Through analysis and simulation, it can be demonstrated that while keeping the probability of missing the return of the primary low, it is possible to detect the emulation attack effectively.