Dissent in Numbers: Making Strong Anonymity Scale

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

239 citations recorded by the source corpus.

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Citations in the corpus

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, background): “These anonymity systems provide strong privacy properties, but require expensive “verifiable mixing” techniques [8, 95], or require work at the servers that is quadratic in the number of client messages sent through the system [38, 121].”
Proactively Accountable Anonymous Messaging in Verdict (2012, methodology): “Dining cryptographers networks [13] (DC-nets) promise security even against traffic analysis attacks, and recent systems such as Herbivore [24, 44] and Dissent [14, 52] have improved the scalability of DC-netstyle systems.”
Riposte: An Anonymous Messaging System Handling Millions of Users (2015, background): “While there is an extensive literature on anonymity systems [22], [28], Riposte offers a combination of security and scalability properties unachievable with current designs.”
SplitX: high-performance private analytics (2013, unknown): “A number of systems utilize the XOR operation [8,29,33], or matrix multiplication [21] to achieve low-cost anonymization without public-key operations.”
Scalable Bias-Resistant Distributed Randomness (2017, background): “Anytrustbased systems, such as Herbivore [32], Dissent [60], and Vuvuzela [59], as well as sharded blockchains [23], use biasresistant public randomness for scalability by sharding participants into smaller groups.”
SGX-LKL: Securing the Host OS Interface for Trusted Execution (2019, background): “cation. For message systems, hiding which users communicate is challenging. Anonymous networks such as Tor [32] are susceptible to trafﬁc analysis attacks [46,72]. Dining Cryptographers (DC) networks [19,91,113] provide stronger guarantees by broadcasting messages to all users, but incur a high over”
Verifying computations without reexecuting them (2015, background): “Across computer systems, we are starting to see a new style of work: reducing sophisticated cryptography and other achievements of theoretical computer science to practice [28, 35, 38, 49].”
Towards efficient traffic-analysis resistant anonymity networks (2013, background): “But, by doing so, they generally have to give up one of bandwidth eﬃciency (e.g., P 5 [26], Dissent [30]), or resistance to traﬃc analysis (e.g., Tor).”
Privacy-preserving deep learning (2015, background): “Scalable anonymous communication protocols with provable security can be used to hide participants’ identities [12, 54].”
Hang with your buddies to resist intersection attacks (2013, methodology): “Anonymous group communication systems, such as DCnets [3, 32, 4] and MIX cascades [24, 1], offer traffic analysis resistance even against powerful adversaries—provided”
Karaoke: Distributed Private Messaging Immune to Passive Traffic Analysis (2018, methodology): “Some systems leak no information to the attacker, using techniques like DC-nets [28], Private Information Retrieval [1], or message broadcast [4].”
Vuvuzela: scalable private messaging resistant to traffic analysis (2015, unknown): “Herbivore [21] and Dissent [36] form broadcast groups of up to 5,000 users each, which limits each user’s anonymity and requires significant overhead to be used for point-to-point communication (as each message is broadcast to all users in its group).”