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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Incentive Mechanism for Cooperative Intrusion Detection: An Evolutionary Game Approach

verfasst von : Yunchuan Guo, Han Zhang, Lingcui Zhang, Liang Fang, Fenghua Li

Erschienen in: Computational Science – ICCS 2018

Verlag: Springer International Publishing

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Abstract

In Mobile Ad-Hoc Networks, cooperative intrusion detection is efficient and scalable to massively parallel attacks. However, due to concerns of privacy leak-age and resource costs, if without enough incentives, most mobile nodes are often selfish and disinterested in helping others to detect an intrusion event, thus an ef-ficient incentive mechanism is required. In this paper, we formulate the incentive mechanism for cooperative intrusion detection as an evolutionary game and achieve an optimal solution to help nodes decide whether to participate in detec-tion or not. Our proposed mechanism can deal with the problems that cooperative nodes do not own complete knowledge about other nodes. We develop a game algorithm to maximize nodes utility. Simulations demonstrate that our strategy can efficiently incentivize potential nodes to cooperate.

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Fußnoten
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Metadaten
Titel
Incentive Mechanism for Cooperative Intrusion Detection: An Evolutionary Game Approach
verfasst von
Yunchuan Guo
Han Zhang
Lingcui Zhang
Liang Fang
Fenghua Li
Copyright-Jahr
2018
Buch
Computational Science – ICCS 2018

Print ISBN: 978-3-319-93697-0

Electronic ISBN: 978-3-319-93698-7

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-93698-7_7