Personal data vaults: a locus of control for personal data streams

  • Authors:

  • Min Mun;Shuai Hao;Nilesh Mishra;Katie Shilton;Jeff Burke;Deborah Estrin;Mark Hansen;Ramesh Govindan

  • Affiliations:

  • University of California, Los Angeles;University of Southern California;University of Southern California;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles;University of California, Los Angeles;University of Southern California

  • Venue:
  • Proceedings of the 6th International COnference
  • Year:
  • 2010

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Abstract

The increasing ubiquity of the mobile phone is creating many opportunities for personal context sensing, and will result in massive databases of individuals' sensitive information incorporating locations, movements, images, text annotations, and even health data. In existing system architectures, users upload their raw (unprocessed or filtered) data streams directly to content-service providers and have little control over their data once they "opt-in". We present Personal Data Vaults (PDVs), a privacy architecture in which individuals retain ownership of their data. Data are routinely filtered before being shared with content-service providers, and users or data custodian services can participate in making controlled data-sharing decisions. Introducing a PDV gives users flexible and granular access control over data. To reduce the burden on users and improve usability, we explore three mechanisms for managing data policies: Granular ACL, Trace-audit and Rule Recommender. We have implemented a proof-of-concept PDV and evaluated it using real data traces collected from two personal participatory sensing applications.