Visible to the public Building Privacy-Aware Computing Systems: An Overview of Current Capabilities and Technical Challenges


Big data analytics has the potential to solve many of the world's pressing problems and to create exciting new opportunities for individuals, corporations and governments. Its applications include finding treatments and cures for diseases, streamlining the world's transportation systems, securing people and infrastructure against acts of terrorism, developing new mechanisms for energy distribution and pricing in smart grids, driving customer-centric businesses in the internet age, and many more. However, the big data requirement appears, almost fundamentally, to be in conflict with the idea of privacy. Indeed, much of big data analytics today involves indiscriminate information gathering with scant regard for individual privacy. How can expressive data analysis be conducted while protecting the privacy of people on whom that data is collected?
In this talk, I will present an overview of the area of privacy-aware computing. The objective is to foster discussions on privacy-aware computing capabilities and the tradeoffs we have to make while using them. I will briefly describe the main players in the big data analytics setting (data owners, data controllers, data users) and discuss their incentives and privacy requirements. Next, I shall describe technical solutions for privacy-aware computing, including beautiful results from cryptography (homomorphic encryption, secure multiparty computation, verifiable computing), and statistical privacy mechanisms (k-anonymity and its variants, differential privacy). For each technique, I shall point out the gap between its capabilities and the requirements imposed by practical systems. These gaps expose several interesting challenges that motivate new research in privacy technologies.


Shantanu Rane received a Ph.D. degree in electrical engineering from Stanford University, California in 2007. His research interests are in applied cryptography, signal processing and information theory. He is currently a Senior Member of the Research Staff at the Palo Alto Research Center (PARC) where he works on problems in privacy-preserving analytics. From 2007-2014, he was with Mitsubishi Electric Research Laboratories (MERL). Shantanu has participated in standardization activity for the Joint Video Team (JVT) under the ITU-T/MPEG H.264/AVC video compression standard, INCITS-M1, the US National Body for standardization of biometrics, and the ISO/IEC JTC1 SC37 Subcommittee on Biometrics. He currently serves as an associate editor for the IEEE Transactions on Information Forensics and Security and the IEEE Signal Processing Magazine.

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