How To Reconcile Big Data and Privacy

Published March 7, 2014   |   
Larry Greenemeier

In many ways “big data” and “encryption” are antithetical. The former involves harvesting, storing and analyzing information to reveal patterns that researchers, law enforcement and industry can use to their benefit. The goal of the latter is to obscure that data from prying eyes. That tension was at the core of a conference this week co-hosted by the White House Office of Science & Technology Policy and the Massachusetts Institute of Technology (M.I.T.), in which more than a dozen experts from academia, politics and industry explored ways encryption and other privacy-oriented technologies might protect the information at involved in big data efforts.

Functional encryption is the way to go, said MIT CSAIL professor Shafi Goldwasser during the panel. Alternatives such as anonymizing data records don’t work, she added. With so much data available about people freely available on social networks and other public sites, anyone looking to do harm can build a profile about their target by cross-referencing information from any number of online resources.

If data is simply being stored, encryption works wonderfully, said Nickolai Zeldovich, an associate professor at the M.I.T. Computer Science and Artificial Intelligence Lab (CSAIL), during Monday’s “Privacy Enhancing Technologies” panel. The trouble comes when you actually need to process and analyze that data. That’s why there is a need for systems that can do practical processing of encrypted data, he added.

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