Sensorsafe: a framework for privacy-preserving management of personal sensory information

  • Authors:

  • Haksoo Choi;Supriyo Chakraborty;Zainul M. Charbiwala;Mani B. Srivastava

  • Affiliations:

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

  • Venue:
  • SDM'11 Proceedings of the 8th VLDB international conference on Secure data management
  • Year:
  • 2011

Quantified Score

Hi-index 0.02

Visualization

Abstract

The widespread use of smartphones and body-worn sensors has made continuous and unobtrusive collection of personal data feasible. This has led to the emergence of useful applications in diverse areas such as medical behavioral studies, personal health-care and participatory sensing. However, the nature of highly personal information shared with these applications, together with the additional inferences that could be possibly drawn using the same data leads to a variety of privacy concerns. This paper proposes SensorSafe, an architecture for managing personal sensory information in a privacy-preserving way. Our architecture consists of multiple remote data stores and a broker so users can retain the ownership of their data and management of multiple users can be well supported. SensorSafe also provides a context-aware ne-grained access control mechanism by which users can dene their own sharing rules based on various conditions including context and behavioral status. We discuss our design of the SensorSafe architecture and provide application examples to show how our system can support user privacy.