Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian/non-Hamiltonian.In this paper a computational complexity theory of the “knowledge” contained in a proof is developed. Zero-knowledge proofs are defined as those proofs that convey no additional knowledge other than the correctness of the proposition in question. Examples of zero-knowledge proof systems are given for the languages of quadratic residuosity and 'quadratic nonresiduosity. These are the first examples of zero-knowledge proofs for languages not known to be efficiently recognizable.

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The knowledge complexity of interactive proof-systems

Trust management and reputation systems in mobile participatory sensing applications

Preserving privacy of feedback providers in decentralized reputation systems

Privacy-respecting reputation systems have been constructed based on anonymous payment systems in order to implement raters' anonymity. To the best of our knowledge, all these systems suffer from the problem of having a "final state", i. e., a system state in which users have no incentive anymore to behave honestly because they reached a maximum reputation or they can no longer be rated. Thus the reputation is in fact no longer lively. We propose a novel approach to address the problem of liveliness by the employment of negative ratings. We tie ratings to actual interactions to force users to also deposit their negative ratings at the reputation server. Otherwise they would not be able to interact any more. Additionally we enhance users' anonymity by limiting timing attacks through the use of transferable-eCash-based payment systems.

https://lirias.kuleuven.be/bitstream/123456789/244794/2/article-1265.pdf

Privacy and Liveliness for Reputation Systems

In this article, we propose an evolution of trust-based recommender systems that only relies on local information and can be deployed on top of existing social networks. Our approach takes into account friends' similarity and confidence on ratings, but limits data exchange to direct friends, in order to prevent ratings from being globally known. Therefore, calculations are limited to locally processed algorithms, privacy concerns can be taken into account and algorithms are suitable for decentralized or peer-to-peer architectures.We have implemented and evaluated our approach against five others, using the Epinions trust network. We show that local information with good default scoring strategies are sufficient to cover more users than classical collaborative filtering and trust-based recommender systems. Regarding accuracy, our approach performs better than most others, specially for cold start users, despite using less information.

Trust-based local and social recommendation

It has been observed that users in a reputation system often hesitate in providing negative feedback due to the fear of retaliation. A solution to this issue is privacy preserving reputation systems, which compute reputation such that the individual feedback of any user is not revealed. In this thesis, we present privacy preserving reputation protocols, that are decentralized, do not require specialized platforms nor trusted third parties, protect privacy under a range of adversarial models (semi-honest, non-disruptive malicious, disruptive malicious), and are more efficient than comparable protocols (the most expensive protocol requires O(n) + O(log N) messages, where n and N are the number of feedback providers and the total number of users respectively). The techniques that we utilize include trust awareness, data perturbation, secret sharing, secure multi-party computation, additive homomorphic cryptosystems, and zero-knowledge proofs. We also address some issues related to trust recommendation and propagation. In particular, we present a solution to the problem of subjectivity in trust recommendation. Experimental results indicate the effectiveness of the proposed strategies.

http://theses.insa-lyon.fr/publication/2010isal0066/these.pdf

Licia Capra

Papers

Privacy Preserving Reputation Systems for Decentralized Environments