Goodness-of-fit-based malicious user detection in cooperative spectrum sensing

Gosan Noh, Sungmook Lim, Seokwon Lee, Daesik Hong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)


Cooperative spectrum sensing improves sensing accuracy in primary user detection, but can be threatened by malicious users. Malicious users may try to falsify the sensing result to indicate that the primary user exists even when there is no primary user in order to monopolize the spectrum usage, thereby depriving other users of their spectrum opportunities. To address this, we propose a malicious user detection scheme where the malicious users are identified and cut off from the cooperative sensing process. The proposed scheme exploits the Anderson-Darling (AD) goodness-of-fit technique which tests whether the empirical distribution of the sensing data from each secondary user fits the expected distribution for a malicious user. In addition, we derive false alarm and detection probabilities for when malicious users are cut off by the malicious user detection scheme. Simulation results show that the proposed goodness-of-fit-based malicious user detection significantly improves sensing performance in comparison with conventional outlier detectionbased schemes.

Original languageEnglish
Title of host publication2012 IEEE Vehicular Technology Conference, VTC Fall 2012 - Proceedings
Publication statusPublished - 2012
Event76th IEEE Vehicular Technology Conference, VTC Fall 2012 - Quebec City, QC, Canada
Duration: 2012 Sept 32012 Sept 6

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252


Other76th IEEE Vehicular Technology Conference, VTC Fall 2012
CityQuebec City, QC

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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