Attacker Detection Based on Dissimilarity of Local Reports in Collaborative Spectrum Sensing

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概要

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• In this letter, we propose a dissimilarity metric (DM) to measure the deviation of a cognitive radio from the network in terms of local sensing reports. Utilizing the probability mass function of the DM, we present a dissimilarity-based attacker detection algorithm to distinguish Byzantine attackers from honest users. The proposed algorithm is able to identify the attackers without a priori information of the attacking styles and is robust against both independent and dependent attacks.

著者

• Wang Jinlong

  Institute Of Communication Engineering Pla University Of Science And Technology

• Wu Qihui

  Institute Of Communication Engineering Pla University Of Science And Technology

• WANG Jinlong

  Institute of Communications Engineering, PLA University of Science and Technology

• YAO Junnan

  Institute of Communications Engineering, PLA University of Science and Technology

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• Attacker Detection Based on Dissimilarity of Local Reports in Collaborative Spectrum Sensing

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