Analysis of primary user emulation attack with motional secondary users in cognitive radio networks

In this paper, we study primary user emulation attacks (PUEA) issue in a cognitive radio network. Most literatures about the PUEA discuss methods to deal with the attacks in a system model where the positions of the primary user and secondary users are fixed. Hence, we focus on the PUEA problem in a system model where the secondary users are motional. Based on the network model with motional secondary users, we discuss how the attacker emulates the primary user. Then, a hybrid PUEA defense strategy based on a combination of energy detection and variance detection is proposed. The performance of the hybrid PUEA defense strategy is analyzed on the premise that the system has particular performance requirements. Simulation results show that our proposed hybrid PUEA defense strategy always performs well. This is the first analytical treatment to study PUEA problem in the scenario with motional secondary users.

[1]  Santhanakrishnan Anand,et al.  Mitigating primary user emulation attacks in dynamic spectrum access networks using hypothesis testing , 2009, MOCO.

[2]  Caidan Zhao,et al.  Anti-PUE Attack Base on the Transmitter Fingerprint Identification in Cognitive Radio , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[3]  Jung-Min Park,et al.  Ensuring Trustworthy Spectrum Sensing in Cognitive Radio Networks , 2006, 2006 1st IEEE Workshop on Networking Technologies for Software Defined Radio Networks.

[4]  Yu-Dong Yao,et al.  Cooperative Spectrum Sensing in Cognitive Radio Networks in the Presence of the Primary User Emulation Attack , 2011, IEEE Transactions on Wireless Communications.

[5]  Han Yu,et al.  Anti-PUE Attack Based on Joint Position Verification in Cognitive Radio Networks , 2010, 2010 International Conference on Communications and Mobile Computing.

[6]  S. Anand,et al.  An Analytical Model for Primary User Emulation Attacks in Cognitive Radio Networks , 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[7]  Erik G. Larsson,et al.  A Bayesian approach to spectrum sensing, denoising and anomaly detection , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[8]  Santhanakrishnan Anand,et al.  Detecting Primary User Emulation Attacks in Dynamic Spectrum Access Networks , 2009, 2009 IEEE International Conference on Communications.

[9]  Sheldon M. Ross,et al.  Introduction to Probability Models, Eighth Edition , 1972 .

[10]  Huifang Chen,et al.  Maximum-minimum eigenvalue detection-based method to mitigate the effect of the PUEA in cognitive radio networks , 2011, 2011 International Conference on Wireless Communications and Signal Processing (WCSP).

[11]  Kouichi Sakurai,et al.  A Differential Game Approach to Mitigating Primary User Emulation Attacks in Cognitive Radio Networks , 2012, 2012 IEEE 26th International Conference on Advanced Information Networking and Applications.

[12]  Carlos A. Pomalaza-Raez,et al.  Modeling primary user emulation attacks and defenses in cognitive radio networks , 2009, 2009 IEEE 28th International Performance Computing and Communications Conference.