Untraceable electronic mail, return addresses, and digital pseudonyms
By A. Rosenberg. 1981
Subfields: Privacy & Security
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Privacy & Security
- Peter Kairouz
- Badih Ghazi
- Rasmus Pagh
- Dan Boneh
- Henry Corrigan-Gibbs
- Jonathan Ullman
- Aleksandra Korolova
- Ninghui Li
Citations in the corpus
- Advances and Open Problems in Federated Learning (2019, background): “Secure shufflers have been studied in the context of secure multi-party computation [95, 251], often under the heading of mix networks.”
- Private Stateful Information Retrieval (2018, background): “That is, the adversary cannot learn the identity of the querying clients which can be enforced by requiring clients to use anonymous mix networks [16].”
- Distributed Differential Privacy via Shuffling (2018, background): “Introduced by [10], the basic idea now exists in many variations.”
- 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].”
- Communication-Efficient Learning of Deep Networks from Decentralized Data (2016, background): “Further, the source of the updates is not needed by the aggregation algorithm, so updates can be transmitted without identifying meta-data over a mix network such as Tor [7] or via a trusted third party.”
- On Safeguarding Privacy and Security in the Framework of Federated Learning (2019, background): “Further, the source of the updates is not needed by the aggregation algorithm, so updates can be transmitted without identifying metadata over a mixed network such as Tor [4] or via a trusted third party.”
- Efficient Private Statistics with Succinct Sketches (2015, methodology): “Work in [24] and [43] provide either k -anonymity [63] and l -diversity [50] to guarantee anonymity of users through Mix Network techniques [17].”
- Riposte: An Anonymous Messaging System Handling Millions of Users (2015, background): “To post a message, the client generates a write request, cryptographically splits it into many shares, and sends one share to each of the Riposte servers.”
- MOCA : MObile Certificate Authority for Wireless Ad Hoc Networks (2004, background): “While there are known approaches to deter traffic analysis in wired networks [5, 6, 20], it is questionable if any of these approaches can be directly applied to ad hoc environments due to their excessive communication and computation overhead.”
- Design Science in Information Systems Research (2004, methodology): “Gavish and Gerdes base their GDSS anonymity designs on past research in the fields of cryptography and secure network communication protocols (e.g., Chaum 1981; Schneier 1996).”
- Wide-area cooperative storage with CFS (2001, methodology): “On the other hand, given a robust location and storage layer, anonymous client access to CFS could be provided by separate anonymizing proxies, using techniques similar to those proposed by Chaum [4] or Reiter and Rubin [27].”
- Five Practical Attacks for "Optimistic Mixing for Exit-Polls" (2003, background): “The notion of a mix-net was invented by Chaum [3] and further developed by a number of people.”
- M2R: Enabling Stronger Privacy in MapReduce Computation (2015, background): “The concept of mix network is first described in the design of untraceable electronic mail [13].”
- How to Leak a Secret: Theory and Applications of Ring Signatures (2001, background): “It also doesn’t work for Bob to send the journalist a message through a standard “anonymizer” [Ch81,Ch88,GRS99], since the anonymizer strips off all source identification and authentication: the journalist would have no reason to believe that the message really came from a cabinet member at all.”
- Optimally Robust Private Information Retrieval (2012, background): “As is common in many distributed privacy-enhancing technologies, such as mix networks [7], Tor [14], or some forms of electronic voting [6], we must assume that some fraction of the servers above some threshold are not colluding against the client.”