Supporting privacy in decentralized additive reputation systems

Elan Pavlov*, Jeffrey S. Rosenschein, Zvi Topol

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

11 Scopus citations

Abstract

Previous studies have been suggestive of the fact that reputation ratings may be provided in a strategic manner for reasons of reciprocation and retaliation, and therefore may not properly reflect the trustworthiness of rated parties. It thus appears that supporting privacy of feedback providers could improve the quality of their ratings. We argue that supporting perfect privacy in decentralized reputation systems is impossible, but as an alternative present three probabilistic schemes that support partial privacy. On the basis of these schemes, we offer three protocols that allow ratings to be privately provided with high probability in decentralized additive reputation systems.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsColli Franzone Colli Franzone, Stefan Poslad, Theo Dimitrakos
PublisherSpringer Verlag
Pages108-119
Number of pages12
ISBN (Print)3540213120, 9783540213123
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2995
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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