Analysis of Cognitive Radio Networks with Security Awareness Employing Channel Sensing

Cognitive radio networks (CRNs) have a great potential in supporting time-critical data delivery among the Internet of Things (IoT) devices and for emerging applications such as smart cities and automation. A wireless channel (radio) about which we have information is called a cognitive radio. However, Cognitive Radio Networks share common resources such as bandwidth or spectrum among several users or stations. Due to continued sharing of resources, cognitive networks often come under security attacks, most common of which are jamming attacks. In the case of jamming attacks, deliberately designed random jamming signals are added to the channel. These jamming signals along with noise result in packet losses and low throughput, degrading the overall performance of the cognitive network. In this work, a security aware jamming rejection mechanism is proposed which detects suspicious signals in the channel frequency response and employs discrete equalization to recover transmitted data. Moreover, this also reduces the effects of noise in the channel. The probability of false alarm has been analyzed with respect to the energy threshold. It has been shown that the probability of false alarm reduced with increase in the energy threshold. A comparative analysis of the proposed work and the previous work [3] shows that the proposed system outperforms the previous work in terms of throughput when analyzed with respect to jamming power and jamming interval. Thus it has been proven that the proposed methodology has been effective in mitigating the effects of the security threats arising out of the jamming activity by possible adversaries. An analysis of probability of false alarm with respect to the energy threshold for energy sensing has also been shown in which it can e clearly shown that as the threshold is lowered, the chances of false alarm increases and vice versa.