Skip to main content
Article
Adaptive Learning of Byzantines' Behavior in Cooperative Spectrum Sensing
2011 IEEE Wireless Communications and Networking Conference (WCNC 2011), March 28-31 2011, Piscataway, NJ
  • Aditya Vempaty, Indian Institute of Technology
  • Keshav Agrawal, Indian Institute of Technology
  • Hao Chen, Boise State University
  • Pramod K. Varshney, Syracuse University
Document Type
Conference Proceeding
Publication Date
3-28-2011
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.
Citation Information
Aditya Vempaty, Keshav Agrawal, Hao Chen and Pramod K. Varshney. "Adaptive Learning of Byzantines' Behavior in Cooperative Spectrum Sensing" 2011 IEEE Wireless Communications and Networking Conference (WCNC 2011), March 28-31 2011, Piscataway, NJ (2011)
Available at: http://works.bepress.com/hao_chen/6/