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

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8258

Full metadata record

DC Field	Value	Language
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
Appears in Collections:	Department of Computer Science and Information Systems

Files in This Item:

There are no files associated with this item.