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Collaborative privacy management: mobile privacy beyond your own devices

Published:11 September 2014Publication History

ABSTRACT

As the development of mobile devices and applications, mobile privacy has become a very important issue. Current researches on mobile privacy mainly focus on potential leakages on a particular device. However, leakage of sensitive data on a mobile device not only violates the privacy of the phone (or data) owner, but also violates the privacy of many other people whose information are contained in the data directly or indirectly (they are called data involvers). To address such problems, we introduce a collaborative privacy management framework, which aims to provide fine-grained data privacy protection for both data owners and data involvers in a distributed manner. Based on individual privacy policies specified by each user, a collaborative privacy policy is generated and enforced on different devices automatically. As a proof-of-concept prototype, we implement the proposed framework on Android and demonstrate its applicability with two case studies.

References

  1. M. Egele, C. Kruegel, E. Kirda, and G. Vigna. PiOS: Detecting privacy leaks in iOS applications. In NDSS, 2011.Google ScholarGoogle Scholar
  2. W. Enck, P. Gilbert, B.-G. Chun, L. P. Cox, J. Jung, P. McDaniel, and A. N. Sheth. Taintdroid: an information-flow tracking system for realtime privacy monitoring on smartphones. In OSDI 10, pages 1--6, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. W. Enck, M. Ongtang, and P. McDaniel. On lightweight mobile phone application certification. In CCS 09, pages 235--245, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. P. Hornyack, S. Han, J. Jung, S. Schechter, and D. Wetherall. These aren't the droids you're looking for: retrofitting Android to protect data from imperious applications. In CCS 11, pages 639--652, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. H. Hu, G.-J. Ahn, and J. Jorgensen. Detecting and resolving privacy conflicts for collaborative data sharing in online social networks. In ACSAC '11, pages 103--112, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. A. C. Squicciarini, M. Shehab, and F. Paci. Collective privacy management in social networks. In WWW'09, pages 521--530, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. R. Stevens, C. Gibler, J. Crussell, J. Erickson, and H. Chen. Investigating user privacy in Android ad libraries. In IEEE Symposium on Security and Privacy 2012 Workshops, 2012.Google ScholarGoogle Scholar
  8. L. Zhang, Y. Guo, and X. Chen. Patronus: Augmented privacy protection for resource publication in online social networks. In MobileCloud 2013, pages 578--583, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Y. Zhou, X. Zhang, X. Jiang, and V. W. Freeh. Taming information-stealing smartphone applications (on Android). In TRUST'11, pages 93--107, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library

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            cover image ACM Conferences
            SPME '14: Proceedings of the ACM MobiCom workshop on Security and privacy in mobile environments
            September 2014
            48 pages
            ISBN:9781450330756
            DOI:10.1145/2646584

            Copyright © 2014 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 11 September 2014

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            Acceptance Rates

            SPME '14 Paper Acceptance Rate7of12submissions,58%Overall Acceptance Rate7of12submissions,58%

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