Smart Traffic-Aware Primary User Emulation Attack and Its Impact on Secondary User Throughput Under Rayleigh Flat Fading Channel

In this paper, an agile smart attacker model in spectrum sensing of cognitive radio network (CRN) is introduced. This smart attacker does not make the channel busy all the time, instead it senses spectrum and when a primary user leaves, it occupies the spectrum by mimicking the signal characteristics of the primary users. To model such a smart attacker, we use a dependent Markov chain to model the primary user and primary user emulation attacker activities, simultaneously. We derive the transition probabilities for the assumed dependent Markov model. Then, the effect of the primary user and attacker traffic on a secondary user's throughput under Rayleigh flat fading channel is investigated and closed form expressions are derived for the average probability of detection and false alarm. Furthermore, the impact of this attacker on the performance of a CRN and the throughput of the secondary user network is studied analytically. We also derive a test rule based on the generalized likelihood ratio test, to detect the legitimate user from smart illegitimate user. In addition, launching primary user emulation attacker in the conventional and proposed smart attacking procedures are compared, where the results demonstrate that by using smart attacking, the deterioration in throughput of the secondary user's network is considerable. In fact, it is shown that under proper selection of the traffic parameters, the secondary user's network throughput may tend toward zero. Finally, the accuracy of the obtained results are analyzed and verified by the simulation results.