Proactively Accountable Anonymous Messaging in Verdict

By Henry Corrigan-Gibbs, David Isaac Wolinsky, Bryan Ford. 2012

109 citations recorded by the source corpus.

Among anonymity systems, DC-nets have long held attraction for their resistance to traffic analysis attacks, but practical implementations remain vulnerable to internal disruption or "jamming" attacks, which require time-consuming detection procedures to resolve. We present Verdict, the first practical anonymous group communication system built using proactively verifiable DC-nets: participants use public-key cryptography to construct DC-net ciphertexts, and use zero-knowledge proofs of knowledge to detect and exclude misbehavior before disruption. We compare three alternative constructions for verifiable DC-nets: one using bilinear maps and two based on simpler ElGamal encryption. While verifiable DC-nets incur higher computational overheads due to the public-key cryptography involved, our experiments suggest that Verdict is practical for anonymous group messaging or microblogging applications, supporting groups of 100 clients at 1 second per round or 1000 clients at 10 seconds per round. Furthermore, we show how existing symmetric-key DC-nets can "fall back" to a verifiable DC-net to quickly identify misbehavior, speeding up previous detections schemes by two orders of magnitude.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Privacy & Security

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Citations in the corpus

Practical Secure Aggregation for Federated Learning on User-Held Data (2016, background): “Recent research has examined the communication efficiencly and operation in the presence of malicious users [5].”
Riposte: An Anonymous Messaging System Handling Millions of Users (2015, methodology): “Recent work [21] uses zero-knowledge techniques to speed up disruption resistance in Dissent (building on ideas of Goll e and Juels [45]).”
Hang with your buddies to resist intersection attacks (2013, methodology): “A further refinement makes submitted Dissent ciphertexts verifiable via cryptographic techniques [12, 5], reducing vulnerability to disruption, and enabling clients to “drop off” ciphertexts and participate even if connectivity is intermittent.”
Practical Secure Aggregation for Privacy-Preserving Machine Learning (2017, background): “Recent research has examined increasing the efﬁciency of DC-nets protocols and allowing them to operate in the presence of malicious users [31].”
A Protocol for Privately Reporting Ad Impressions at Scale (2016, background): “These run the range from improvements to Tor [41], to alternatives [31, 33, 35], to a line of works on scalable mixnets [20, 21], and dining cryptographer networks [17, 43, 18].”