Adaptive learning of byzantines' behavior in cooperative spectrum sensing

Aditya Vempaty, Keshav Agrawal, Hao Chen, Pramod Varshney

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

61 Scopus citations

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 α (percentage of Byzantines). It has also been shown that these estimates of Pfa and PD of the Byzantines are asymptotically unbiased and converge to their true values at the rate of 0(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.

Original languageEnglish
Title of host publication2011 IEEE Wireless Communications and Networking Conference, WCNC 2011
Pages1310-1315
Number of pages6
DOIs
StatePublished - 2011
Event2011 IEEE Wireless Communications and Networking Conference, WCNC 2011 - Cancun, Mexico
Duration: 28 Mar 201131 Mar 2011

Publication series

Name2011 IEEE Wireless Communications and Networking Conference, WCNC 2011

Conference

Conference2011 IEEE Wireless Communications and Networking Conference, WCNC 2011
Country/TerritoryMexico
CityCancun
Period28/03/1131/03/11

Keywords

  • Byzantine AttacksC
  • Byzantine Attacksognitive Radio Networks
  • ognitive Radio Networks
  • Spectrum Sensing

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