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CS Talk In this talk I will describe my past, ongoing and planned work towards this goal. The first part of this research program — now nearing completion — is to demonstrate the inadequacy of the current paradigm by developing reidentification and statistical inference algorithms for various types of “anonymized” data: our preferences, transactions, social relationships, and behavior. The second part is to develop an approach to building systems based on lightweight cryptography, a hybrid of centralized and decentralized architectures, and incorporation of policy-based defenses. I will describe how I have applied these principles to my work on location privacy and behavioral ad targeting. Bio: Arvind Narayanan is a post-doctoral computer science
researcher at Stanford and a junior affiliate scholar at the Stanford
Law School Center for Internet and Society. He completed his Ph.D at UT
Austin in 2009. Narayanan studies information privacy and security, and
moonlights in policy. His paper on deanonymization of large datasets won
the 2008 Privacy Enhancing Technologies award and his 2011 paper on location
privacy at NDSS won the distinguished paper award.
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