Biblio

Software-defined wireless sensor cognitive radio network is one of the emerging technologies which is simple, agile, and flexible. The sensor network comprises of a sink node with high processing power. The sensed data is transferred to the sink node in a hop-by-hop basis by sensor nodes. The network is programmable, automated, agile, and flexible. The sensor nodes are equipped with cognitive radios, which sense available spectrum bands and transmit sensed data on available bands, which improves spectrum utilization. Unfortunately, the Software-defined wireless sensor cognitive radio network is prone to security issues. The sinkhole attack is the most common attack which can also be used to launch other attacks. We propose and evaluate the performance of Hop Count-Based Sinkhole Attack detection Algorithm (HCOBASAA) using probability of detection, probability of false negative, and probability of false positive as the performance metrics. On average HCOBASAA managed to yield 100%, 75%, and 70% probability of detection.

The ever-increasing number of wireless network systems brought a problem of spectrum congestion leading to slow data communications. All of the radio spectrums are allocated to different users, services and applications. Hence studies have shown that some of those spectrum bands are underutilized while others are congested. Cognitive radio concept has evolved to solve the problem of spectrum congestion by allowing cognitive users to opportunistically utilize the underutilized spectrum while minimizing interference with other users. Byzantine attack is one of the security issues which threaten the successful deployment of this technology. Byzantine attack is compromised cognitive radios which relay falsified data about the availability of the spectrum to other legitimate cognitive radios in the network leading interference. In this paper we are proposing a security measure to thwart the effect caused by these attacks and compared it to Attack-Proof Cooperative Spectrum Sensing.