Transcription of De-anonymizing Web Browsing Data with Social …
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De-anonymizing Web Browsing Data with Social …
De-anonymizing Web Browsing data with Social NetworksJessica SuStanford ShuklaStanford GoelStanford NarayananPrinceton online trackers and network adversaries de-anonymizeweb Browsing data readily available to them? We show theoretically, via simulation, and through experiments onreal user data that de-identified web Browsing histories canbe linked to Social media profiles using only publicly avail-able data . Our approach is based on a simple observation:each person has a distinctive Social network , and thus theset of links appearing in one s feed is unique. Assumingusers visit links in their feed with higher probability thana random user, Browsing histories contain tell-tale marks ofidentity. We formalize this intuition by specifying a modelof web Browsing behavior and then deriving the maximumlikelihood estimate of a user s Social profile.
De-anonymizing Web Browsing Data with Social Networks Jessica Su Stanford University jtysu@stanford.edu Ansh Shukla Stanford University anshukla@stanford.edu
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