Malicious user detection for wide-band cognitive radio networks

In cooperative spectrum sensing, malicious user (MU) sends tampered sensing result in spectrum sensing to pose threats to cognitive radio networks, which is called spectrum sensing data falsification (SSDF) attack. Many existing MU detection schemes are designed for the narrow-band environment. However, Research on MU detection schemes for compressive sensing (CS), which has some huge advantages in sensing wide-band spectrum, is just beginning. Because of the high complex of reconstruction algorithms, it's necessary to identify potential MU and then exclude the MU before reconstructing the original signal in CS. In this paper, we consider attack and defense behavior in CS and propose a density-based MU detection (DBMUD) with a trusted user to distinguish MU precisely. DBMUD maintains reliability even if MUs are a majority. Simulation results demonstrate that DBMUD performs well in fighting against SSDF attack.