A New Method to Detect Primary User Emulation Attacks in Cognitive Radio Networks

Abstract

Abstract-Cognitive radio (CR) can improve the utilization of the spectrum by making use of licensed spectrum in an opportunistic manner. However, the security aspects of cognitive radio networks have garnered little attention. In this paper, we identify a threat to cognitive radio networks, which we call the primary user emulation (PUE) attack. To counter this threat, we proposed a new method to detect the PUE attacks which not only discuss in two kinds of situation which the primary user is stationary or mobile, but also use the Kalman filter algorithm to process the received mobile source's signal strength (RSS) value. And then, we apply with the BP neural network training and testing to complete the detection of PUE attacks. Simulations results show the goodness of the proposed method.

A survey on security attacks and countermeasures with primary user detection in cognitive radio networks

“…Blesa et al [55] state that countermeasures based on geo-location are not appropriate for scenarios with mobile PUs and SUs, and, according to Araujo et al [42], mobile attackers can take advantage of their mobility in order to remain undetected. We note that Peng, Zeng, and Zeng [56] propose what they argue to be the first PU emulation detection solution considering mobile attackers. Xin and Song [5] present a PU emulation attack detection scheme, designated as Signal Activity Pattern Acquisition and Reconstruction System (SPARS), which does not use any a priori knowledge of PUs.…”

“…The estimation of the distances to the transmitters of the received signals using RSS values is employed by most of the existing proposals addressing the detection of PU emulation attacks [56]. However, as the transmission power of attackers is not known by the SUs and can vary over time if they have power control capabilities, estimating the distance to the sources of the signals requires additional features.…”