Performance analysis of probabilistic soft SSDF attack in cooperative spectrum sensing

In cognitive radio networks, spectrum sensing data falsification (SSDF) attack is a crucial factor deteriorating the detection performance of cooperative spectrum sensing. In this paper, we propose and analyze a novel probabilistic soft SSDF attack model, which goes beyond the existing models for its generalization. Under this generalized SSDF attack model, we firstly obtain closed form expressions of global sensing performance at the fusion center. Then, we theoretically evaluate the performance of the proposed attack model, in terms of destructiveness and stealthiness, sequentially. Numerical simulations match the analytical results well. Last but not least, an interesting trade-off between destructiveness and stealthiness is discovered, which is a fundamental issue involved in SSDF attack, however, ignored by most of the previous studies.