Confidentialité dans les systèmes de réputation
Grégory Bonnet1 ; Laurent Vercouter2 ; Damien Lelerre1
1 Normandie Université, UNICAEN, ENSICAEN, CNRS, GREYC, Caen, France
2 Normandie Université, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, Rouen, France
Revue Ouverte d'Intelligence Artificielle, Post-actes des Journées Francophones sur les Systèmes Multi-Agents (JFSMA 2018-2019-2020), Volume 3 (2022) no. 5-6, pp. 671-689.

Dans les systèmes de réputation, il a été observé, qu’afin d’éviter des évaluations vengeresses, les témoignages étaient majoritairement positifs, réduisant par là-même l’efficacité du système. Pour inciter les agents à diffuser tous leurs témoignages, les solutions classiques proposent d’anonymiser les témoignages. Dans la littérature, de nombreux travaux ont étudé des approches cryptographiques pour s’assurer à la fois de l’anonymat et de la non-répudiation des témoignages. Toutefois, ceci ne permet de garantir leur confidentialité en raison des corrélations entre transactions et diffusion d’un nouveau témoignage. Dans cet article, nous proposons d’étudier la faisabilité d’une autre approche dans laquelle les témoignages sont bruités et soumis à des délais de diffusion. Des résultats d’expérimentation mettent en lumière l’effet de ces perturbations sur les systèmes de réputation BetaReputation et EigenTrust.

On reputation systems, it has been observed that testimonies are mostly positive in order to avoid vengeful evaluations. Such behaviour reduces the effectiveness of the system. In order to incite agents to publish all their testimonies, classic solutions consist in anonymizing them. In the literature, many works have proposed cryptographic approaches to ensure both anonymity and non-repudiation of testimonies. However, due to correlations between transactions and dissemination of new testimonies, it does not guarantee confidentiality. In this article, we propose to study the feasibility of another approach in which a noise is applied on testimonies and those latter are subject to delays of diffusion. Experimental results highlight the effect of these disturbances on the BetaReputation and EigenTrust reputation systems.

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DOI : 10.5802/roia.47
Mots-clés : Systèmes multi-agents, Systèmes de confiance et de réputation, Confidentialité
Keywords: Multi-agent systems, Trust and reputation systems, Confidentiality

Grégory Bonnet 1 ; Laurent Vercouter 2 ; Damien Lelerre 1

1 Normandie Université, UNICAEN, ENSICAEN, CNRS, GREYC, Caen, France
2 Normandie Université, UNIROUEN, UNIHAVRE, INSA Rouen, LITIS, Rouen, France
Licence : CC-BY 4.0
Droits d'auteur : Les auteurs conservent leurs droits 
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     title = {Confidentialit\'e dans les syst\`emes de r\'eputation},
     journal = {Revue Ouverte d'Intelligence Artificielle},
     pages = {671--689},
     publisher = {Association pour la diffusion de la recherche francophone en intelligence artificielle},
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Grégory Bonnet; Laurent Vercouter; Damien Lelerre. Confidentialité dans les systèmes de réputation. Revue Ouverte d'Intelligence Artificielle, Post-actes des Journées Francophones sur les Systèmes Multi-Agents (JFSMA 2018-2019-2020), Volume 3 (2022) no. 5-6, pp. 671-689. doi : 10.5802/roia.47. https://roia.centre-mersenne.org/articles/10.5802/roia.47/

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