CCR: A Model for Sharing Reputation Knowledge Across Virtual Communities

Grinshpoun, Tal; Gal-Oz, Nurit; Meisels, Amnon; Gudes, Ehud

doi:10.1109/wi-iat.2009.13

Cited by 26 publications

(16 citation statements)

References 11 publications

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“…after every expert/member interaction). Another issue is the private computation and presentation (amount of drill-down) of reputation information in case reputation is accumulated from multiple communities (see [15]). …”

Section: Discussionmentioning

confidence: 99%

Schemes for Privately Computing Trust and Reputation

Gal-Oz¹,

Gilboa²,

Gudes³

2010

IFIP Advances in Information and Communication Technology

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Abstract. Trust and Reputation systems in distributed environments attain widespread interest as online communities are becoming an inherent part of the daily routine of Internet users. Several models for Trust and Reputation have been suggested recently, among them the Knots model [8]. The Knots model provides a member of a community with a method to compute the reputation of other community members. Reputation in this model is subjective and tailored to the taste and choices of the computing member and those members that have similar views, i.e. the computing member's Trust-Set. A discussion on privately computing trust in the Knots model appears in [16]. The present paper extends and improves [16] by presenting three efficient and private protocols to compute trust in trust based reputation systems that use any trust-sets based model. The protocols in the paper are rigorously proved to be private against a semi-honest adversary given standard assumptions on the existence of an homomorphic, semantically secure, public key encryption system. The protocols are analyzed and compared in terms of their privacy characteristics and communication complexity.

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Section: Discussionmentioning

confidence: 99%

Schemes for Privately Computing Trust and Reputation

Gal-Oz¹,

Gilboa²,

Gudes³

2010

IFIP Advances in Information and Communication Technology

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“…In this section we briefly describe the way reputation is aggregated from several communities using the CCR model [9,5]. The CCR model defines the major stages required to aggregate the reputation of a community member with the reputation of that member in other communities.…”

Section: Aggregation and Cross Community Reputationmentioning

confidence: 99%

“…Thus the need arises to aggregate reputation from multiple communities. We developed the Cross-Community Reputation (CCR) model for the sharing of reputation knowledge across virtual communities [5,6,9]. The CCR model is aimed at leveraging reputation data from multiple communities to obtain more accurate reputation.…”

Section: Introductionmentioning

confidence: 99%

Reputation - from Social Perception to Internet Security

Gudes

2015

Trust Management IX

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Abstract. Reputation is a concept that we use in many aspects of our social life and as part of our decision making process. We use reputation in our interaction with people or companies we do not know and we use it when we buy merchandize or reserve a room in a hotel. However, reputation plays also an important role in the internet society and enables us to establish trust which is essential for interaction in the virtual world. Reputation has several important aspects such as Aggregation, Identity and Transitivity which make it applicable in completely different domains. In this presentation we show the use of these aspects in several different domains and demonstrate it with our own previous and current research on reputation.A good name is more desirable than great riches; to be esteemed is better than silver or gold. Proverbs 22:1

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“…In [31], Grinshpoun et al, introduce a Cross-Community Reputation (CCR) model. They argue that reputation information sourced from multiple communities is more accurate, and removes the need to bootstrap a new reputation for every new community.…”

Section: Slashdotmentioning

confidence: 99%

Malleable Access Rights to Establish and Enable Scientific Collaboration

Hendrikx

Bubendorfer

2013

2013 IEEE 9th International Conference on E-Science

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Abstract-Collaborative systems require access control to prevent unauthorised access and change. Access control has a number of issues, including administration and maintenance overheads. In this paper we argue that it is time to reconsider how access controls work, particularly with scientific and data related domains, and to this end we propose a new paradigm based on a user's demographics and behaviour, rather than simply their identity. In essence, it is both who you are and what you do that is important. We introduce GRAft, our Generalised Recommendation Architecture that allows us to support a range of different recommendation models, and provide case studies to illustrate the usefulness of our architecture.

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CCR: A Model for Sharing Reputation Knowledge Across Virtual Communities

Cited by 26 publications

References 11 publications

Schemes for Privately Computing Trust and Reputation

Schemes for Privately Computing Trust and Reputation

Reputation - from Social Perception to Internet Security

Malleable Access Rights to Establish and Enable Scientific Collaboration

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