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dc.contributor.authorBehfarnia, Ali
dc.contributor.authorEslami, Ali
dc.identifier.citationA. Behfarnia and A. Eslami, "Local Voting Games for Misbehavior Detection in VANETs in Presence of Uncertainty," 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, IL, USA, 2019, pp. 480-486en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractCooperation between neighboring vehicles is an effective solution to the problem of malicious node identification in vehicular ad hoc networks (VANETs). However, the outcome is subject to nodes' beliefs and reactions in the collaboration. In this paper, a plain game-theoretic approach that captures the uncertainty of nodes about their monitoring systems, the type of their neighboring nodes, and the outcome of the cooperation is proposed. In particular, one stage of a local voting-based scheme (game) for identifying a target node is developed using a Bayesian game. In this context, incentives are offered in expected utilities of nodes in order to promote cooperation in the network. The proposed model is then analyzed to obtain equilibrium points, ensuring that no node can improve its utility by changing its strategy. Finally, the behavior of malicious and benign nodes is studied by extensive simulation results. Specifically, it is shown how the existing uncertainties and the designed incentives impact the strategies of the players and, consequently, the correct target-node identification.en_US
dc.description.sponsorshipNational Science Foundation under Award No. OIA-1656006 and matching support from the State of Kansas through the Kansas Board of Regents.en_US
dc.relation.ispartofseries57th Annual Allerton Conference on Communication, Control, and Computing (Allerton);2019
dc.subjectGame theoryen_US
dc.subjectlocal voting-based schemeen_US
dc.subjectMisbehavior detectionen_US
dc.titleLocal voting games for misbehavior detection in VANETs in presence of uncertaintyen_US
dc.typeConference paperen_US
dc.rights.holder© 2019, IEEEen_US

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