Cryptology ePrint Archive: Report 2014/502

What's the Gist? Privacy-Preserving Aggregation of User Profiles

Igor Bilogrevic and Julien Freudiger and Emiliano De Cristofaro and Ersin Uzun

Abstract: Over the past few years, online service providers have started gathering increasing amounts of personal information to build user profiles and monetize them with advertisers and data brokers. Users have little control of what information is processed and are often left with an all-or-nothing decision between receiving free services or refusing to be profiled. This paper explores an alternative approach where users only disclose an aggregate model -- the ``gist'' -- of their data. We aim to preserve data utility and simultaneously provide user privacy. We show that this approach can be efficiently supported by letting users contribute encrypted and differentially-private data to an aggregator. The aggregator combines encrypted contributions and can only extract an aggregate model of the underlying data. We evaluate our framework on a dataset of 100,000 U.S. users obtained from the U.S. Census Bureau and show that (i) it provides accurate aggregates with as little as 100 users, (ii) it generates revenue for both users and data brokers, and (iii) its overhead is appreciably low.

Category / Keywords: applications / privacy

Original Publication (in the same form): ESORICS 2014

Date: received 25 Jun 2014, last revised 27 Jun 2014

Contact author: me at emilianodc com

Available format(s): PDF | BibTeX Citation

Version: 20140627:114831 (All versions of this report)

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