Robust De-anonymization of Large Sparse Datasets
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Cites background from "Robust De-anonymization of Large Sp..."
...However, the widespread availability of extensive records of individual behavior, together with the desire to learnmore about customers and citizens, presents serious challenges related to privacy and data ownership (4, 5)....
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2,156 citations
Cites background from "Robust De-anonymization of Large Sp..."
...Narayananan [32] demonstrated that an adversary with some prior knowledge can identify a subscriber’s record in the anonymized Netflix prize dataset....
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...A number of works have focused on attacks that result from access to (even anonymized) data [18,29,32,38]....
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1,957 citations
Additional excerpts
...capturing a few of their votes [111]....
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References
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"Robust De-anonymization of Large Sp..." refers methods in this paper
...We now quantify the amount of auxiliary information needed to de-anonymize an arbitrary dataset using Algorithm Scoreboard....
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"Robust De-anonymization of Large Sp..." refers background in this paper
...This does not guarantee any privacy, because the values of sensitive attributes associated with a given quasi-identifier may not be sufficiently diverse [20, 21] or the adversary may know more than just the quasiidentifiers [20]....
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3,629 citations
"Robust De-anonymization of Large Sp..." refers background in this paper
...Other possible countermeasures include interactive mechanisms for privacy-protecting data mining such as [5, 12], as well as more recent non-interactive techniques [6]....
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