Robust Algorithm Against Spectrum Sensing Data Falsification Attack in Cognitive Radio Networks

Abstract : One of the main challenges in cooperative spectrum sensing (CSS) for cognitive radio networks (CRN) is spectrum sensing falsification (SSDF) attack. A SSDF attack consists in a cognitive user providing false data about the spectrum status. SSDF attack can hugely degrade the achievable detection accuracy and energy efficiency of CRNs. In this paper, a robust CSS algorithm against SSDF attack is proposed. The proposed algorithm assigns a specific weight to each user, which is able to (i) completely eliminate the resulting effects on CSS caused by many types of SSDF attacks, (ii) convert some types of SSDF attacks to be honest users, and (iii) alleviate the influence of other honest users that suffer from poor sensing performance or/and very noisy reporting channels. Simulation results show that, compared to many previous works, a significant improvement in detection accuracy and energy efficiency can be attained by the proposed algorithm.
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Communication dans un congrès
2014 IEEE 79th Vehicular Technology Conference (VTC Spring), May 2014, Seoul, South Korea. Proceedings of the 2014 IEEE Vehicular Technology Conference, 〈10.1109/vtcspring.2014.7023078 〉
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https://hal-supelec.archives-ouvertes.fr/hal-01104514
Contributeur : Wei Lu <>
Soumis le : vendredi 16 janvier 2015 - 20:29:00
Dernière modification le : jeudi 5 avril 2018 - 12:30:23

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Saud Althunibat, Marco Di Renzo, Granelli Fabrizio. Robust Algorithm Against Spectrum Sensing Data Falsification Attack in Cognitive Radio Networks. 2014 IEEE 79th Vehicular Technology Conference (VTC Spring), May 2014, Seoul, South Korea. Proceedings of the 2014 IEEE Vehicular Technology Conference, 〈10.1109/vtcspring.2014.7023078 〉. 〈hal-01104514〉

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