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

62 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 (Pf a ) and detection (P D ). 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 a 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 (Q e ) and compare it with the minimum probability of error possible.

Original languageAmerican English
Title of host publication2011 IEEE Wireless Communications and Networking Conference, WCNC 2011
Pages1310-1315
Number of pages6
DOIs
StatePublished - 28 Mar 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), March 28-31 2011, Piscataway, NJ

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

EGS Disciplines

  • Electrical and Computer Engineering

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