Skip to main content
SpringerLink
Log in
Book cover

Workshop on Secure Data Management

SDM 2011: Secure Data Management pp 85–100Cite as

SensorSafe: A Framework for Privacy-Preserving Management of Personal Sensory Information

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6933))

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.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. FieldStream: network data services for exposure biology studies in natural environments, http://www.fieldstream.org/

  2. Google health, http://www.google.com/intl/en/health/about/

  3. Institutional Review Board - Protect Research Data, http://irb.ufl.edu/irb01/data.html

  4. JavaScript object notation, http://www.json.org/

  5. Microsoft HealthVault, http://www.healthvault.com

  6. Philips DirectLife: fitness, health and successful weight management, http://www.directlife.philips.com/

  7. Zephyr technology corporation, BioHarness BT, http://www.zephyr-technology.com/bioharness-bt

  8. Ahmadi, H., Pham, N., Ganti, R., Abdelzaher, T., Nath, S., Han, J.: Privacy-aware regression modeling of participatory sensing data. In: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, pp. 99–112 (2010)

    Google Scholar 

  9. Baden, R., Bender, A., Spring, N., Bhattacharjee, B., Starin, D.: Persona: an online social network with user-defined privacy. ACM SIGCOMM Computer Communication Review 39(4), 135–146 (2009)

    Article  Google Scholar 

  10. Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.: Participatory sensing. In: World Sensor Web Workshop, pp. 1–5 (2006)

    Google Scholar 

  11. Cáceres, R., Cox, L., Lim, H., Shakimov, A., Varshavsky, A.: Virtual individual servers as privacy-preserving proxies for mobile devices. In: Proc. of the 1st ACM Workshop on Networking, Systems, and Applications for Mobile Handhelds, pp. 37–42 (2009)

    Google Scholar 

  12. Candes, E., Romberg, J., Tao, T.: Stable signal recovery from incomplete and inaccurate measurements. Communications on Pure and Applied Mathematics 59(8), 1207–1223 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  13. Chang, K., Yau, N., Hansen, M., Estrin, D.: Sensorbase.org: a centralized repository to slog sensor network data. In: Proc. of the International Conf. on Distributed Networks (DCOSS)/EAWMS (2006)

    Google Scholar 

  14. Cornelius, C., Kapadia, A., Kotz, D., Peebles, D., Shin, M., Triandopoulos, N.: AnonySense: Privacy-aware people-centric sensing. In: Proc. of the 6th International Conference on Mobile Systems, Applications, and Services, pp. 211–224 (2008)

    Google Scholar 

  15. Cornwell, J., Fette, I., Hsieh, G., Prabaker, M., Rao, J., Tang, K., Vaniea, K., Bauer, L., Cranor, L., Hong, J., et al.: User-controllable security and privacy for pervasive computing. In: Proc. of the 8th IEEE Workshop on Mobile Computing Systems and Applications, pp. 14–19 (2007)

    Google Scholar 

  16. Fung, B.C., Wang, K., Chen, R., Yu, P.S.: Privacy-preserving data publishing: A survey on recent developments. ACM Computing Surveys (2010)

    Google Scholar 

  17. Ganti, R., Pham, N., Tsai, Y., Abdelzaher, T.: PoolView: stream privacy for grassroots participatory sensing. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 281–294 (2008)

    Google Scholar 

  18. Girod, L., Mei, Y., Newton, R., Rost, S., Thiagarajan, A., Balakrishnan, H., Madden, S.: XStream: a Signal-Oriented Data Stream Management System. In: Proc. of IEEE 24th International Conference on Data Engineering, pp. 1180–1189 (2008)

    Google Scholar 

  19. Hansell, S.: AOL removes search data on vast group of web users. New York Times (August 8, 2006)

    Google Scholar 

  20. Hoh, B., Gruteser, M., Herring, R., Ban, J., Work, D., Herrera, J., Bayen, A., Annavaram, M., Jacobson, Q.: Virtual trip lines for distributed privacy-preserving traffic monitoring. In: Proc. of the 6th International Conference on Mobile Systems, Applications, and Services, pp. 17–20 (2008)

    Google Scholar 

  21. Jain, A., Chang, E.: Adaptive sampling for sensor networks. In: Proc. of the 1st International Workshop on Data Management for Sensor Networks: in Conjunction with VLDB 2004, pp. 10–16 (2004)

    Google Scholar 

  22. Kotz, D., Avancha, S., Baxi, A.: A privacy framework for mobile health and home-care systems. In: Proc. of the first ACM Workshop on Security and Privacy in Medical and Home-care Systems, pp. 1–12 (2009)

    Google Scholar 

  23. Krumm, J.: Inference attacks on location tracks. In: LaMarca, A., Langheinrich, M., Truong, K.N. (eds.) Pervasive 2007. LNCS, vol. 4480, pp. 127–143. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  24. Li, N., Li, T., Venkatasubramanian, S.: t-Closeness: privacy beyond k-Anonymity and l-Diversity. In: Proc. of IEEE 23rd International Conference on Data Engineering, pp. 106–115 (2007)

    Google Scholar 

  25. Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: L-diversity: Privacy beyond k-anonymity. ACM Transactions on Knowledge Discovery from Data (March 2007)

    Google Scholar 

  26. Miluzzo, E., Lane, N., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S., Zheng, X., Campbell, A.: Sensing meets mobile social networks: the design, implementation and evaluation of the cenceme application. In: Proc. of the 6th ACM Conference on Embedded Network Sensor Systems, pp. 337–350 (2008)

    Google Scholar 

  27. Mun, M., Hao, S., Mishra, N., Shilton, K., Burke, J., Estrin, D., Hansen, M., Govindan, R.: Personal data vaults: a locus of control for personal data streams. In: Proc. of the 6th International Conference, p. 17 (2010)

    Google Scholar 

  28. Mun, M., Reddy, S., Shilton, K., Yau, N., Burke, J., Estrin, D., Hansen, M., Howard, E., West, R., Boda, P.: PEIR, the personal environmental impact report, as a platform for participatory sensing systems research. In: Proc. of 7th International Conference on Mobile Systems, Applications, and Services, pp. 55–68 (2009)

    Google Scholar 

  29. Narayanan, A., Shmatikov, V.: Robust de-anonymization of large sparse datasets. In: Proc. of IEEE Symposium on Security and Privacy, pp. 111–125 (2008)

    Google Scholar 

  30. Narayanan, A., Shmatikov, V.: De-anonymizing social networks. In: Proc. of IEEE Symposium on Security and Privacy, pp. 173–187 (2009)

    Google Scholar 

  31. Plarre, K., Raij, A., Hossain, S.M., Ali, A.A., Nakajima, M., al’Absi, M., Ertin, E., Kamarck, T., Kumar, S., Scott, M., Siewiorek, D., Smailagic, A., Wittmers Jr., L.E.: Continuous inference of psychological stress from sensory measurements collected in the natural environment. In: Proc. of 10th International Conference on Information Processing in Sensor Networks (2011)

    Google Scholar 

  32. Raij, A., Ghosh, A., Kumar, S., Srivastava, M.: Privacy risks emerging from the adoption of innocuouswearable sensors in the mobile environment. In: Proc. of ACM CHI Conference on Human Factors in Computing Systems (2011)

    Google Scholar 

  33. Reddy, S., Burke, J., Estrin, D., Hansen, M., Srivastava, M.: Determining transportation mode on mobile phones. In: Proc. of 12th IEEE International Symposium on Wearable Computers, pp. 25–28 (2008)

    Google Scholar 

  34. Seong, S., Seo, J., Nasielski, M., Sengupta, D., Hangal, S., Teh, S., Chu, R., Dodson, B., Lam, M.: PrPl: a decentralized social networking infrastructure. In: Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond, pp. 1–8 (2010)

    Google Scholar 

  35. Sweeney, L.: k-anonymity: a model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 10, 557–570 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  36. Toch, E., Cranshaw, J., Hankes-Drielsma, P., Springfield, J., Kelley, P.G., Cranor, L., Hong, J., Sadeh, N.: Locaccino: a privacy-centric location sharing application. In: Proc. of 12th ACM International Conference on Ubiquitous Computing, pp. 381–382 (2010)

    Google Scholar 

  37. Tootoonchian, A., Saroiu, S., Ganjali, Y., Wolman, A.: Lockr: better privacy for social networks. In: Proc. of the 5th International Conference on Emerging Networking Experiments and Technologies, pp. 169–180 (2009)

    Google Scholar 

  38. Wikipedia. Personal health record, http://en.wikipedia.org/wiki/Personal_health_record

Download references

Author information

Authors and Affiliations

  1. University of California, Los Angeles, USA

    Haksoo Choi, Supriyo Chakraborty, Zainul M. Charbiwala & Mani B. Srivastava

Authors
  1. Haksoo Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Supriyo Chakraborty
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zainul M. Charbiwala
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mani B. Srivastava
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O.Box 217, 7500 AE, Enschede, The Netherlands

    Willem Jonker

  2. Philips Research Europe, High Tech Campus 34 (office 3.14), 5656 AE, Eindhoven, The Netherlands

    Milan Petković

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Choi, H., Chakraborty, S., Charbiwala, Z.M., Srivastava, M.B. (2011). SensorSafe: A Framework for Privacy-Preserving Management of Personal Sensory Information. In: Jonker, W., Petković, M. (eds) Secure Data Management. SDM 2011. Lecture Notes in Computer Science, vol 6933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23556-6_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23556-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23555-9

  • Online ISBN: 978-3-642-23556-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation