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Securing overlay activities of peers in unstructured P2P networks

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dc.contributor.authorPark, Jun-Cheol-
dc.contributor.authorYu, Geonu-
dc.date.accessioned2022-07-05T08:42:11Z-
dc.date.available2022-07-05T08:42:11Z-
dc.date.created2022-07-05-
dc.date.issued2007-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/29911-
dc.description.abstractThis paper dismisses how to secure overlay activities of peers on overlay level messages exchanged in unstructured P2P networks. We identify some attacks that can be effectively handled by appropriate cryptographic means. We then give a detection method against those attacks including message modification, replay attack, and message generation with wrong information. The method presumes the existence of a set of CAs, which are consulted when peers are newly joining the network and otherwise uninvolved in the peer activities. We also address the attack of a peer's illegal dropping of relaying messages, which is hard to be traced to its doer even with the assist of cryptographic means. We propose an audit and topology adaptation technique to confine and weaken the ill effect of such an attack on other peers in the network. We demonstrate the effectiveness of the technique using a modified GnutellaSim [14] simulator with respect to various metrics. Being based upon a generic overlay model, the proposed techniques can be applied to any unstructured P2P network either separately or all together.-
dc.language영어-
dc.language.isoen-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleSecuring overlay activities of peers in unstructured P2P networks-
dc.typeArticle-
dc.contributor.affiliatedAuthorPark, Jun-Cheol-
dc.identifier.wosid000251348000083-
dc.identifier.bibliographicCitationCOMPUTATIONAL INTELLIGENCE AND SECURITY, v.4456, pp.795 - +-
dc.relation.isPartOfCOMPUTATIONAL INTELLIGENCE AND SECURITY-
dc.citation.titleCOMPUTATIONAL INTELLIGENCE AND SECURITY-
dc.citation.volume4456-
dc.citation.startPage795-
dc.citation.endPage+-
dc.type.rimsART-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
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