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• W2119978040 abstract "This paper considers the problem of Byzantine attacks on cooperative spectrum sensing in cognitive radio networks. Our major contribution is a technique to learn about the cognitive radio (CR) potential malicious behavior over time and thereby identifies the Byzantines and then estimates their probabilities of false alarm (Pf <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>a</sub> ) and detection (P <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>D</sub> ). We show that for a given set of data over time, the Byzantines can be identified for any a (percentage of Byzantines). It has also been shown that these estimates of Pf <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>a</sub> and Pn of the Byzantines are asymptotically unbiased and converge to their true values at the rate of O(T <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>-1/2</sup> ). We then use these probabilities to adaptively design the fusion rule. We calculate the Probability of error (Q <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>e</sub> ) and compare it with the minimum probability of error possible." @default.
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• W2119978040 date "2011-03-01" @default.
• W2119978040 modified "2023-09-26" @default.
• W2119978040 title "Adaptive learning of Byzantines' behavior in cooperative spectrum sensing" @default.
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• W2119978040 doi "https://doi.org/10.1109/wcnc.2011.5779320" @default.
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