(A) recursive updating algorithm with aging factor and order statistics for cognitive radio networks under SSDF attacks

Abstract

In this thesis, we propose a detection scheme based on the recursive updating algorithm with aging factor and order statistics for cooperative cognitive radio networks under spectrum sensing data falsification (SSDF) attacks. By introducing an aging factor into the recursive updating algorithm in calculating the reputation degree of each secondary user (SU), the proposed scheme not only is sensitive to the change in the behavior of SUs but also allows reduction in the storage space. In addition, to eliminate the influence of malicious users, order statistics are incorporated in selecting SUs with higher reputation degree for cooperation. It is shown through computer simulations that the proposed scheme can defend the network against the SSDF attacks effectively.