Identiﬁed the Netﬂix records of known users, uncovering their apparent

Movie Database<<< as the source of background knowledge, we successfully Identify this subscriber’s record in the dataset. Knows only a little bit about an individual subscriber can easily Movie ratings of 500,000 subscribers of Netﬂix, the world’s largest Methodology to the Netﬂix Prize dataset, which contains anonymous Robust to perturbation in the data and tolerate some mistakes in theĪdversary’s background knowledge. Recommendations, transaction records and so on. High-dimensional micro-data, such as individual preferences, We present a new class of statistical de-anonymization attacks against It's quite a famous paper and was even on the news when it got published. The University of Texas at Austin February 5, 2008. 'Robust De-anonymization of Large Datasets (How to Break Anonymity of the Netﬂix Prize Dataset)'. So in reading this question I HAVE to point this out - ever heard of the paper?:Īrvind Narayanan and Vitaly Shmatikov. Not sure if this would classify as a comment or an answer, but it's useful information nonethelss:

Imdb data file converter