Hermitan matrices based malicious cognitive radio detection and bayesian method for detecting primary user emulation attack

Cognitive radio (CR) is a facilitating technology to efficiently deal with the spectrum scarceness, and it will significantly enhance deployment of upcoming wireless transmission method. Security significant concern, although not well tackle in cognitive networks (CRN). In CR networks, this approach regard as security issue happen from primary user emulation attack (PUEA). A PUEA attacker forwards an emulated signal defraud users avoid them accessing holes. Here, we introduce Hermitan matrices based malicious (CMCR) detection Bayesian method for detecting CRN. approach, used attack. The trust analyzer evaluates trust. node value computed by activeness inactiveness, degree data transmission, hermitan matrics verification. addition, Matrices detect simulation outcomes propose that CMCR leads improve performance terms better ratio, minimized possibility miss ratio. Furthermore, false alarm