A robust and knot-aware trust-based reputation model

Nurit Gal-Oz, Ehud Gudes, Danny Hendler

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations


Virtual communities become more and more heterogeneous as their scale increases. This implies that, rather than being a single, homogeneous community, they become a collection of knots (or sub-communities) of users. For the computation of a member's reputation to be useful, the system must therefore identify the community knot to which this member belongs and to interpret its reputation data correctly. Unfortunately, to the best of our knowledge existing trust-based reputation models treat a community as a single entity and do not explicitly address this issue. In this paper, we introduce the knot-aware trust-based reputation model for large-scale virtual communities. We define a knot as a group of community members having overall "strong" trust relations between them. Different knots typically represent different view points and preferences. It is therefore plausible that the reputation of the same member in different knots assign may differ significantly. Using our knot-aware approach, we can deal with heterogeneous communities where a member's reputation may be distributed in a multi modal manner. As we show, an interesting and beneficial feature of our knot-aware model is that it naturally prevents malicious attempts to bias community members' reputation.

Original languageEnglish
Title of host publicationTrust Management II
Subtitle of host publicationProceedings of IFIPTM 2008: Joint iTrust and PST Conferences on Privacy, Trust Management and Security
EditorsYücel Karabulut, Mitchell Mitchell, Peter Herrmann, Christian Damsgaard Jensen
Number of pages16
StatePublished - 27 May 2008


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