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Issue No.05 - May (2014 vol.13)
pp: 1022-1034
M. Song , Department of Electrical Engineering and Computer Science, University of Toledo, Toledo, OH, USA
Promising to significantly improve spectrum utilization, cognitive radio networks (CRNs) have attracted a great attention in the literature. Nevertheless, a new security threat known as the primary user emulation (PUE) attack raises a great challenge to CRNs. The PUE attack is unique to CRNs and can cause severe denial of service (DoS) to CRNs. In this paper, we propose a novel PUE detection system, termed Signal activity Pattern Acquisition and Reconstruction System. Different from current solutions of PUE detection, the proposed system does not need any a priori knowledge of primary users (PUs), and has no limitation on the type of PUs that are applicable. It acquires the activity pattern of a signal through spectrum sensing, such as the ON and OFF periods of the signal. Then it reconstructs the observed signal activity pattern through a reconstruction model. By examining the reconstruction error, the proposed system can smartly distinguish a signal activity pattern of a PU from a signal activity pattern of an attacker. Numerical results show that the proposed system has excellent performance in detecting PUE attacks.
Data models, Probability distribution, Training, Sensors, Training data, Radio transmitters,
M. Song, "Detection of PUE Attacks in Cognitive Radio Networks Based on Signal Activity Pattern", IEEE Transactions on Mobile Computing, vol.13, no. 5, pp. 1022-1034, May 2014, doi:10.1109/TMC.2013.121
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