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Trust-Aware Peer Sampling: Performance and Privacy Tradeoffs

Abstract : The ability to identify people that share one's own interests is one of the most interesting promises of the Web 2.0 driving user-centric applications such as recommendation systems or collaborative marketplaces. To be truly useful, however, information about other users also needs to be associated with some notion of trust. Consider a user wishing to sell a concert ticket. Not only must she find someone who is interested in the concert, but she must also make sure she can trust this person to pay for it. This paper addresses the need for trust in user-centric applications by propos- ing two novel distributed protocols that combine interest-based connections be- tween users with explicit links obtained from social networks à-la Facebook. Both protocols build trusted multi-hop paths between users in an explicit so- cial network supporting the creation of semantic overlays backed up by social trust. The first protocol, TAPS2 , extends our previous work on TAPS (Trust- Aware Peer Sampling), by improving the ability to locate trusted nodes. Yet, it remains vulnerable to attackers wishing to learn about trust values between ar- bitrary pairs of users. The second protocol, PTAPS (Private TAPS ), improves TAPS2 with provable privacy guarantees by preventing users from revealing their friendship links to users that are more than two hops away in the social network. In addition to proving this privacy property, we evaluate the per- formance of our protocols through event-based simulations, showing significant improvements over the state of the art.
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https://hal.inria.fr/hal-00872996
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Submitted on : Monday, October 14, 2013 - 8:38:21 PM
Last modification on : Tuesday, June 15, 2021 - 4:31:15 PM
Long-term archiving on: : Friday, April 7, 2017 - 10:53:52 AM

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  • HAL Id : hal-00872996, version 1

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Davide Frey, Arnaud Jégou, Anne-Marie Kermarrec, Michel Raynal, Julien Stainer. Trust-Aware Peer Sampling: Performance and Privacy Tradeoffs. Theoretical Computer Science, Elsevier, 2013. ⟨hal-00872996⟩

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