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This page contains all of the posts and discussion on MemeStreams referencing the following web page: How To Break Anonymity of the Netflix Prize Dataset. You can find discussions on MemeStreams as you surf the web, even if you aren't a MemeStreams member, using the Threads Bookmarklet.

How To Break Anonymity of the Netflix Prize Dataset
by possibly noteworthy at 5:25 pm EST, Nov 26, 2007

Anonymity is Hard.

We present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge.

We apply our de-anonymization methodology to the Netflix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netflix, the world's largest online movie rental service. We demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. Using the Internet Movie Database as the source of background knowledge, we successfully identified the Netflix records of known users, uncovering their apparent political preferences and other potentially sensitive information.

See also:

Hushmail Spills it to Feds

AOL Search Database

Why Information Security is Hard

Don Kerr, on Anonymity and Privacy

Seeing Corporate Fingerprints in Wikipedia Edits

WikiScanner on the Colbert Report


 
 
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