Efficient anonymity-preserving data collection

By Justin Brickell, Vitaly Shmatikov. 2006

80 citations recorded by the source corpus.

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In Artificial Intelligence

Citations in the corpus

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, background): “Other data-collection systems have clients send their private data to an aggregator through a general-purpose anonymizing network, such as a mix-net [27, 32, 47, 87] or a DC-net [31, 38–40, 110].”
Proactively Accountable Anonymous Messaging in Verdict (2012, background): “Dissent [14, 52] uses verifiable shuffles [10, 36] to establish a transmission schedule for DC-nets, enabling groups to guarantee a one-to-one correspondence of group members to anonymous transmission slots.”
This Paper Is Included in the Proceedings of the 12th Usenix Symposium on Operating Systems Design and Implementation (osdi '16). Unobservable Communication over Fully Untrusted Infrastructure Unobservable Communication over Fully Untrusted Infrastructure (unknown): “There are proposals that do not require trusting the communication infrastructure [26] [33] [42] [60] [66] [131], but they have been primarily theoretical since the resulting systems support only dozens of concurrent users.”
CoinShuffle: Practical Decentralized Coin Mixing for Bitcoin (2014, methodology): “This shuffling is inspired from one phase of the accountable anonymous group messaging protocol Dissent [28, 38], which builds on an anonymous data collection protocol due to Brickell and Shmatikov [39].”
Hang with your buddies to resist intersection attacks (2013, background): “While “ad hoc” mix-nets and onion routing schemes are vulnerable to many traffic analysis and active attacks, variants such as MIX cascades [5,7,41] and verifiable shuffles [25, 39] offer formally provable traffic analysis resistance.”
Dissent: accountable anonymous group messaging (2010, methodology): “protocol ensures integrity and anonymity exactly as in its precursor [7], but our new go/no-go and blame phases enable all group members to trace the culprit of any protocol malfunction.”
Dissent in Numbers: Making Strong Anonymity Scale (2012, unknown): “Two other approaches to anonymity theoretically offer security even against traffic analysis: verifiable shuffles [11, 32, 44], and “dining cryptographers” or DCnets [14, 36, 58].”