Mitigation of the Spectrum Sensing Data Falsifying Attack in Cognitive Radio Networks

Rajorshi Biswas, Jie Wu, Xiaojiang Du

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

6 Scopus citations

Abstract

Cognitive radio networks (CRNs), offering novel network architecture for utilizing spectrum, have attracted significant attention in recent years. In CRNs, secondary users (SUs) first determine the status of a channel; if it is free, they start transmitting. If the status determination is wrong, SUs may unnecessarily interfere with the licensed primary user (PU). In cooperative spectrum sensing, a SU makes a decision about the presence of the PU based on its own and other SUs' sensing results. Malicious SUs (MSUs) send false sensing results to SUs so that they make wrong decisions about the PU presence. As a result, a SU may transmit during the presence of the PU or may keep starving for the spectrum. In this paper, we propose a reputation-based mechanism for cooperative spectrum sensing which can minimize the effects of MSUs on decision making. Some of the SUs are selected as distributed fusion centers (DFCs), which are responsible for making decisions about the PU presence and inform the reporting SUs. A DFC uses weighted majority voting among the reporting SUs, where weights are determined based on reputation. The DFC updates reputations of SUs based on confidence of an election. If the majority wins by a significant margin, the confidence of the election is high. In this case, SUs that belong to the majority get high reputations. We provide extensive simulations to validate our proposed model.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
ISBN (Electronic)9781538680889
DOIs
StatePublished - May 2019
Event2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
Duration: 20 May 201924 May 2019

Publication series

NameIEEE International Conference on Communications
Volume2019-May
ISSN (Print)1550-3607

Conference

Conference2019 IEEE International Conference on Communications, ICC 2019
Country/TerritoryChina
CityShanghai
Period20/05/1924/05/19

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