Adaptive learning of byzantines' behavior in cooperative spectrum sensing

Aditya Vempaty, Keshav Agrawal, Hao Chen, Pramod Varshney

Research output: Chapter in Book/Entry/PoemConference contribution

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 (US)
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: Mar 28 2011Mar 31 2011

Publication series

Name2011 IEEE Wireless Communications and Networking Conference, WCNC 2011

Other

Other2011 IEEE Wireless Communications and Networking Conference, WCNC 2011
Country/TerritoryMexico
CityCancun
Period3/28/113/31/11

Keywords

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

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Communication

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