Can Privacy be Free?

Speaker
John Canny
Computer Science, UC Berkeley, and Berkeley Institute of Design

When
-

Where
Newell-Simon Hall 1305 (Michael Mauldin Auditorium)

Description

The digital environment we live in has many conveniences, but it has also created many risks to privacy. We often focus on the visible aspects of this—the increasing use of cameras, tags etc. But its important to remember that our *digital* presence is routinely monitored, and that there are real risks *today* from this—loss of job, damage to credit, medical insurability etc. There is a necessary tension between providers who can offer better services if they know more about us, and the risks to us from other use of this data. In our work we attempt to resolve this tension by developing privacy-preserving algorithms for a class of services. A key challenge in developing these methods is economic. Users want privacy but are not willing to pay for it. Providers have no direct incentive to provide privacy either, but some are willing if there is no cost. Recently we developed an architecture called P4P or “Peers For Privacy” which supports a broad class of services at essentially the same cost (including constant factors) as the “normal” services. There is no loss in accuracy in P4P, which is important since lower accuracy often translates to lower revenue for personalized services. P4P exploits the natural incentives and “social capital” among a user community to provide the resources to add privacy. I will describe our ongoing work with P4P including a recently-completed implementation in Java.

Speaker's Bio

John Canny is the Paul and Stacy Jacobs Distinguished Professor of Engineering. His research is in human-computer interaction, with an emphasis on modeling methods (usually probabilistic) and privacy approaches using cryptography. He received his Ph.D. in 1987 at the MIT AI Lab. His dissertation on Robot Motion Planning received the ACM dissertation award. He received a Packard Foundation Faculty Fellowship and a Presidential Young Investigator Award. His peer-reviewed publications span robotics, computational geometry, physical simulation, computational algebra, theory and algorithms, information retrieval, HCI and CSCW and cryptography. He has best-paper prizes in IEEE FOCS, ECAI (European AI Conference) and AAAI.

Speaker's Website
http://www.cs.berkeley.edu/~jfc/

Host
Jennifer Mankoff