I looked at the methods used in the paper and it's clear that my definition of "privacy" varies greatly from the author's definition. Essentially they are sayi

I looked at the methods used in the paper and it's clear that my definition of "privacy" varies greatly from the author's definition. Essentially they are saying that if you know what rating someone gave 8 movies and the date that they gave those ratings, you can find a sample of their rating list (or something very similar to it) with 99% accuracy. So freaking what? "Evidence" that flimsy wouldn't stand up in a local bar argument, much less a court of law. The records are still completely and totally anonymous. No names, no addresses, no way to identify anyone...nothing but a strong statistical correlation to a set of ratings in a database. It sounds like they have a problem with the power of predictive modeling and not with the handling of anonymous data. Esstentially what they are saying is "if we know a little about you, we find can out things that we didn't know with a very high degree of accuracy, but no certainty.". Duh. That's what the whole netflix prize was about...using known data to make strong predictions about unknowns. They had some interesting methods (especially in their similarity calculations) but this has nothing to do with privacy.