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Detecting Sybils in Peer-to-Peer Overlays Using Psychometric Analysis Methods

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dc.contributor.author Haribabu, K
dc.date.accessioned 2023-01-03T09:49:57Z
dc.date.available 2023-01-03T09:49:57Z
dc.date.issued 2011
dc.identifier.uri https://ieeexplore.ieee.org/document/5763448
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8258
dc.description.abstract Peer to peer networks are fast becoming the most popular file sharing media, guaranteeing complete user anonymity to the clients. However, modern P2P networks suffer from Sybil attacks, which forge multiple identities to influence the global decisions in the network. This paper suggests a novel solution to minimize Sybils influence using unique combination of Psychometric Tests, Color Tests & CAPTCHAs. Our survey has shown that the proposed approach is promising in detecting not just Sybils but Sybil groups. The results have shown that 30-50% of Sybil groups are detected. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Computer Science en_US
dc.subject P2P networks en_US
dc.subject Sybil Detection en_US
dc.subject Psychometric Analysis en_US
dc.title Detecting Sybils in Peer-to-Peer Overlays Using Psychometric Analysis Methods en_US
dc.type Article en_US


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