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dc.contributor.authorKwon, Albert
dc.contributor.authorCorrigan-Gibbs, Henry
dc.contributor.authorDevadas, Srinivas
dc.contributor.authorFord, Bryan
dc.date.accessioned2021-11-05T16:46:03Z
dc.date.available2021-11-05T16:46:03Z
dc.date.issued2017-10
dc.identifier.urihttps://hdl.handle.net/1721.1/137543
dc.description.abstract© 2017 Copyright held by the owner/author(s). Publication rights licensed to Association for Computing Machinery. Atom is an anonymous messaging system that protects against traffic-analysis attacks. Unlike many prior systems, each Atom server touches only a small fraction of the total messages routed through the network. As a result, the system’s capacity scales near-linearly with the number of servers. At the same time, each Atom user benefits from “best possible” anonymity: a user is anonymous among all honest users of the system, even against an active adversary who monitors the entire network, a portion of the system’s servers, and any number of malicious users. The architectural ideas behind Atom have been known in theory, but putting them into practice requires new techniques for (1) avoiding heavy general-purpose multi-party computation protocols, (2) defeating active attacks by malicious servers at minimal performance cost, and (3) handling server failure and churn. Atom is most suitable for sending a large number of short messages, as in a microblogging application or a high-security communication bootstrapping (“dialing”) for private messaging systems. We show that, on a heterogeneous network of 1,024 servers, Atom can transit a million Tweet-length messages in 28 minutes. This is over 23× faster than prior systems with similar privacy guarantees.en_US
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionof10.1145/3132747.3132755en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleAtom: Horizontally Scaling Strong Anonymityen_US
dc.typeArticleen_US
dc.identifier.citationKwon, Albert, Corrigan-Gibbs, Henry, Devadas, Srinivas and Ford, Bryan. 2017. "Atom: Horizontally Scaling Strong Anonymity."
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-05-28T16:23:07Z
dspace.date.submission2019-05-28T16:23:08Z
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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