AnonRep: Towards Tracking-Resistant Anonymous Reputation
Ennan Zhai, Yale University; David Isaac Wolinsky, Facebook, Inc.; Ruichuan Chen, Nokia Bell Labs; Ewa Syta, Yale University; Chao Teng, Facebook, Inc.; Bryan Ford, École Polytechnique Fédérale de Lausanne (EPFL)
Reputation systems help users evaluate information quality and incentivize civilized behavior, often by tallying feedback from other users such as "likes" or votes and linking these scores to a user’s long-term identity. This identity linkage enables user tracking, however, and appears at odds with strong privacy or anonymity. This paper presents AnonRep, a practical anonymous reputation system offering the benefits of reputation without enabling long-term tracking. AnonRep users anonymously post messages, which they can verifiably tag with their reputation scores without leaking sensitive information. AnonRep reliably tallies other users’ feedback (e.g., likes or votes) without revealing the user’s identity or exact score to anyone, while maintaining security against score tampering or duplicate feedback. A working prototype demonstrates that AnonRep scales linearly with the number of participating users. Experiments show that the latency for a user to generate anonymous feedback is less than ten seconds in a 10,000-user anonymity group
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author = {Ennan Zhai and David Isaac Wolinsky and Ruichuan Chen and Ewa Syta and Chao Teng and Bryan Ford},
title = {{AnonRep}: Towards {Tracking-Resistant} Anonymous Reputation},
booktitle = {13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16)},
year = {2016},
isbn = {978-1-931971-29-4},
address = {Santa Clara, CA},
pages = {583--596},
url = {https://www.usenix.org/conference/nsdi16/technical-sessions/presentation/zhai},
publisher = {USENIX Association},
month = mar
}
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