Two-Tier Optimal-Cooperation Based Secure Distributed Spectrum Sensing for Wireless Cognitive Radio Networks

We study security issues that may pose a serious threat to the spectrum sensing for wireless cognitive radio networks. In particular, we focus on two of the main security threats: Incumbent Emulation (IE) attacks and Spectrum Sensing Data Falsification (SSDF) attacks. We develop a Distributed Spectrum Sensing (DSS) algorithm to defend against each of the two attacks in a two-tier cognitive radio network. For the IE attacks, we develop a user verification scheme, called localization-based defense. For the SSDF attacks, we propose an optimal nonlinear cooperation scheme, which minimizes the interference to the primary emulation attack. To take the more realistic scenarios into account, we characterize the DSS algorithm as an M-ary Hypotheses problem, and formulate it as an optimization problem by introducing a deflection coefficient. The simulation results evaluate our proposed optimal nonlinear cooperation scheme and validate the significant cooperative gain achieved.