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• W2137351625 abstract "There has been a flurry of research on leveraging social networks to defend against multiple identity, or Sybil, attacks. A series of recent works does not try to explicitly identify Sybil identities and, instead, bounds the impact that Sybil identities can have. We call these approaches Sybil tolerance; they have shown to be effective in applications including reputation systems, spam protection, online auctions, and content rating systems. All of these approaches use a social network as a credit network, rendering multiple identities ineffective to an attacker without a commensurate increase in social links to honest users (which are assumed to be hard to obtain). Unfortunately, a hurdle to practical adoption is that Sybil tolerance relies on computationally expensive network analysis, thereby limiting widespread deployment." @default.
• W2137351625 created "2016-06-24" @default.
• W2137351625 creator A5002813297 @default.
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• W2137351625 creator A5022718146 @default.
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• W2137351625 date "2012-04-10" @default.
• W2137351625 modified "2023-09-23" @default.
• W2137351625 title "Canal" @default.
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• W2137351625 doi "https://doi.org/10.1145/2168836.2168867" @default.
• W2137351625 hasPublicationYear "2012" @default.
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