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Anonymity and Rewards in Peer Rating Systems

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Security and Cryptography for Networks (SCN 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12238))

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Abstract

When peers rate each other, they may rate inaccurately to boost their own reputation or unfairly lower another’s. This could be mitigated by having a reputation server incentivise accurate ratings with a reward. However, assigning rewards becomes challenging when ratings are anonymous, since the reputation server cannot tell which peers to reward for rating accurately. To address this, we propose an anonymous peer rating system in which users can be rewarded for accurate ratings, and we formally define its model and security requirements. In our system ratings are rewarded in batches, so that users claiming their rewards only reveal they authored one in this batch of ratings. To ensure the anonymity set of rewarded users is not reduced, we also split the reputation server into two entities, the Rewarder, who knows which ratings are rewarded, and the Reputation Holder, who knows which users were rewarded. We give a provably secure construction satisfying all the security properties required. For our construction we use a modification of a Direct Anonymous Attestation scheme to ensure that peers can prove their own reputation when rating others, and that multiple feedback on the same subject can be detected. We then use Linkable Ring Signatures to enable peers to be rewarded for their accurate ratings, while still ensuring that ratings are anonymous. Our work results in a system which allows accurate ratings to be rewarded, whilst still providing anonymity of ratings with respect to the central entities managing the system.

L. Garms—The author was supported by the EPSRC and the UK government as part of the Centre for Doctoral Training in Cyber Security at Royal Holloway, University of London (EP/K035584/1) and by the InnovateUK funded project AQuaSec.

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Notes

  1. 1.

    Traceability here refers to the requirement that multiple ratings cannot be given on the same subject per round.

  2. 2.

    For example, in  [50], \(f_1\) is simply the number of incentives received multiplied by some weight, and \(f_2\) is the weighted sum of these components.

  3. 3.

    We require a secure channel to prevent the Reputation Holder from accessing the ratings, and determining which ratings will be rewarded by following the strategy of the Rewarder. This knowledge would allow the Reputation Holder to decrease the anonymity set of the users claiming incentives, as in the case when both the Rewarder and Reputation Holder are corrupted.

  4. 4.

    The case of a corrupt Rewarder is captured in the Anonymity of Ratings under Full Corruption requirement.

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Authors and Affiliations

  1. Royal Holloway, University of London, Egham, UK

    Lydia Garms, Siaw–Lynn Ng & Elizabeth A. Quaglia

  2. Cysec, Lausanne, Switzerland

    Giulia Traverso

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  1. Lydia Garms
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  2. Siaw–Lynn Ng
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  3. Elizabeth A. Quaglia
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  4. Giulia Traverso
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Correspondence to Lydia Garms .

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  1. Università degli Studi di Salerno, Fisciano, Italy

    Clemente Galdi

  2. Georgia Institute of Technology, Atlanta, GA, USA

    Vladimir Kolesnikov

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Garms, L., Ng, S., Quaglia, E.A., Traverso, G. (2020). Anonymity and Rewards in Peer Rating Systems. In: Galdi, C., Kolesnikov, V. (eds) Security and Cryptography for Networks. SCN 2020. Lecture Notes in Computer Science(), vol 12238. Springer, Cham. https://doi.org/10.1007/978-3-030-57990-6_14

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