LAUSR

The study and the detection of possible network attacks are essential for wireless networks, in particular for mobile cognitive radio networks due to its characteristics such as the dynamic spectrum allocation and constant frequency hopping. The primary user emulation attack is one of the most significant attacks in cognitive radio, because it hazards the complete cognitive cycle. The techniques used for the detection of primary user emulation found in the literature are based on a fixed attacker location. However, in a mobile environment, the attacker usually has dynamic locations and this compromises the current applied security techniques and generates inefficient attack detection. Therefore, our work proposes a novel technique using cross-layer design for the detection of primary user emulation with mobility. This attack detection technique was tested with experiments using software-defined radio equipment and mobile phones at indoor scenarios with dynamic locations and with a mobile phone base station built up also with software-defined radio. The obtained results show that the combination of the three utilized techniques, energy detection, motion estimation, and application information analysis, are able to optimize the detection with around 100% of effectiveness for the primary user emulation attack with dynamic location. The proposed technique shows that the energy detection time is around 100 ms and for the processing time of the information analysis in the mobile phone is about 30 s. This result shows a practical and effective approach to detect primary emulation attacks. The proposed technique, to the best of the authors’ knowledge, has not been presented before in the literature with experiments neither with mobility conditions of the attacker as presented in our proposed work.