Detecting Multi-ChannelWireless Microphone User Emulation Attacks in White Space with Noise

Cognitive radio networks (CRNs) are susceptible to primary user emulation (PUE) attacks. Conventional PUE attack detection approaches consider television broadcasting as the primary user. In this work, however, we study a special kind of PUE attack named wireless microphone user emulation (WMUE) attack. Existing work on WMUE attack detection deals with single channel senario. Although multi-channelWM(MCWM) systems are common, detecting WMUE attacks under a multi-channel setting in noisy environments has not been well studied. In this work, we propose a novelmulti-channelWMUEattack detection scheme which operates in low signal-to-noise ratio (SNR) environments with low computational complexity, thanks to the first 1.5-bit FM demodulator whose outputs are represented by only 0, 1 and -1. Experimental results show that, the proposed scheme can effectively detect multi-channel WMUE attacks within 0.25 second when SNR is lower than 6 dB