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Adaptive Learning of Byzantines' Behavior in Cooperative Spectrum Sensing

Aditya Vempaty, Indian Institute of Technology
Keshav Agrawal, Indian Institute of Technology
Hao Chen, Boise State University
Pramod K. Varshney, Syracuse University

Article comments

2011 IEEE Wireless Communications and Networking Conference (WCNC 2011), March 28-31 2011, Piscataway, NJ. DOI: 10.1109/WCNC.2011.5779320

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 (Pfa) and detection (PD). 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 Pfa and Pn of the Byzantines are asymptotically unbiased and converge to their true values at the rate of O(T-1/2). We then use these probabilities to adaptively design the fusion rule. We calculate the Probability of error (Qe) and compare it with the minimum probability of error possible.

Suggested Citation

Aditya Vempaty, Keshav Agrawal, Hao Chen, and Pramod K. Varshney. "Adaptive Learning of Byzantines' Behavior in Cooperative Spectrum Sensing" IEEE Wireless Communications and Networking Conference (2011).
Available at: http://works.bepress.com/hao_chen/6