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Dynamic mix zone: location data sanitizing in assisted environments

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Abstract

Pervasive technology has been widely used in assistive environments and aware homes. The issue of how to preserve the privacy of patients being monitored has been attracting more public concerns. In assistive environments, location data of patients are collected through sensors for behavior patterns analysis, and they can also be shared among researchers for further research for early disease diagnosis. However, location information, even though de-identified, also introduces the risk of privacy leakage. A series of consecutive location samples can be considered as a trajectory of a single person, and this may leak private information if obtained by malicious users. This paper discusses this problem and proposes a location randomization algorithm to protect users’ location privacy. Two privacy metrics according to location privacy are defined and used to evaluate the proposed approach. A method using dynamic mix zones is proposed to confound trajectories of two or more persons.

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References

  1. Beresford, A.R., Stajano, F.: Mix zones: user privacy in location-aware services. In: Second IEEE Annual Conference on Pervasive Computing and Communications Workshops, p. 127. IEEE (2004)

  2. Hoh, B., Gruteser, M.: Protecting location privacy through path confusion. In: First International Conference on Security and Privacy for Emerging Areas in Communications Networks, 2005. Secure communication (2005)

  3. Ackerman, L., Kempf, J., Miki, T.: Wireless location privacy: a report on law and policy in the United States, the European union, and Japan. DoCoMo USA Labs Technical Report DCL-TR2003-001 (2003)

  4. Snekkenes, E.: Concepts for personal location privacy policies. In: Proceedings of the 3rd ACM Conference on Electronic Commerce, pp. 48–57. ACM Press (2001). doi:10.1145/501158.501164

  5. Schilit, B., Hong, J., Gruteser, M.: Wireless location privacy protection. IEEE Comput. 135–137 (2003)

  6. Beresford, A.R., Stajano, F.: Location privacy in pervasive computing. IEEE Pervasive Comput. 2(1), 46–55 (2003). doi:10.1109/MPRV.2003.1186725

    Google Scholar 

  7. Gruteser, M., Schelle, G., Jain, A., Han, R., Grunwald, D.: Privacy-aware location sensor networks. In: HotOS IX: 9th USENIX Workshop on Hot Topics in Operating Systems (2003)

  8. Gruteser, M., Grunwald, D.: Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of the First International Conference on Mobile Systems, Applications, and Services (MobiSys). USENIX (2003)

  9. Gunter, C.A., May, M.J., Stubblebine, S.: A formal privacy system and its application to location based services. In: Privacy Enhancing Technologies (PET) (2004)

  10. Fowler, R.J., Paterson, M.S., Tanimoto, S.L.: Optimal packing and covering in the plane are NP-complete. Inf. Process. Lett. 12(3): 133–137 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  11. Bronnimann, H., Goodrich, M.T.: Almost optimal set covers in finite VC-dimension: (preliminary version). In: SCG ’94: Proceedings of the Tenth Annual Symposium on Computational Geometry, pp. 293–302 (1994)

  12. Gonzales, T.: Covering a set of points in multidimensional space. Inf. Process. Lett. 40(4), 181–188 (1991)

    Article  Google Scholar 

  13. Hochbaum, D., Maass, W.: Approximation schemes for covering and packing problems in image processing and VLSI. J. ACM 32(1), 130–136 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  14. Franceschetti M., Cook M., Bruck J.: A geometric theorem for network design. IEEE Trans. Comput. 53(4), 483–489 (2004)

    Article  Google Scholar 

  15. Durbin, J., Koopman, S.J.: Time Series Analysis by State Space Methods. Oxford University Press Inc., New York (2001)

    MATH  Google Scholar 

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Authors and Affiliations

  1. Computer Science and Engineering Department, University of Texas at Arlington, Arlington, TX, USA

    Zhengyi Le, Yi Ouyang & Fillia Makedon

  2. Computer Science Department, University of Massachusetts at Lowell, Lowell, MA, USA

    Guanling Chen

Authors
  1. Zhengyi Le
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  2. Yi Ouyang
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  3. Guanling Chen
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  4. Fillia Makedon
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Corresponding author

Correspondence to Zhengyi Le.

Additional information

This work was supported in part by the National Science Foundation under award number ITR 0733674, IDM 0733673, and CT-ISG 0716261. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Le, Z., Ouyang, Y., Chen, G. et al. Dynamic mix zone: location data sanitizing in assisted environments. Univ Access Inf Soc 10, 195–205 (2011). https://doi.org/10.1007/s10209-010-0198-4

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  • DOI: https://doi.org/10.1007/s10209-010-0198-4

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