PROJECT TITLE :

Cross-Layer Design for Primary User Emulation Attacks Detection in Mobile Cognitive Radio Networks

ABSTRACT:

In this letter, the channel-tap power is used as a radio-frequency fingerprint (RF) to utterly identify primary user emulation attacks (PUEAs) over multipath Rayleigh fading channels. To accurately know identities of primary users (PUs) and PUEAs, the cross-layer intelligent learning ability of a mobile secondary user (SU) is exploited to establish detection databases by seamlessly combining the short detection of physical (PHY) layer with the accuracy of higher layer authentication. The proposed methodology helps PHY layer completely detect the identities of PUs and PUEAs. For and therefore the false alarm chance of 0.one, the SU will detect a PUEA with the detection probability of zero.9673 under the mobile speed of 70 km/h.


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