Skip to main content

Privacy-Preserving Statistical Analysis on Ubiquitous Health Data

  • Conference paper
Trust, Privacy and Security in Digital Business (TrustBus 2011)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 6863))

Abstract

In this work, we consider ubiquitous health data generated from wearable sensors in a Ubiquitous Health Monitoring System (UHMS) and examine how these data can be used within privacy- preserving distributed statistical analysis. To this end, we propose a secure multi-party computation based on a privacy-preserving cryptographic protocol that accepts as input current or archived values of users’ wearable sensors. We describe a prototype implementation of the proposed solution with a community of independent personal agents and present preliminary results that confirm the viability of the approach.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Acquisti, A., Gritzalis, S., Lambrinoudakis, C., De Capitani di Vimercati, S.: Digital privacy. Auerbach Publications, Taylor & Francis Group (2008)

    Google Scholar 

  2. Aggarwal, C.C.: On k-anonymity and the curse of dimensionality. In: VLDB 2005, pp. 901–909 (2005)

    Google Scholar 

  3. Bouncycastle Java Library (January 2011), http://www.bouncycastle.org/

  4. Camous, F., McCann, D., Roantree, M.: Capturing personal health data from wearable sensors. In: SAINT 2008, pp. 153–156. IEEE, Los Alamitos (2008)

    Google Scholar 

  5. Ciriani, V., Capitani di Vimercati, S., Foresti, S., Samarati, P.: κ-anonymity. In: Secure Data Management in Decentralized Systems. Advances in Information Security, vol. 33, pp. 323–353. Springer, Heidelberg (2007)

    Google Scholar 

  6. Drosatos, G., Efraimidis, P.S.: Privacy-enhanced management of ubiquitous health monitoring data. In: PETRA 2011. ACM, New York (2011)

    Google Scholar 

  7. Drosatos, G., Efraimidis, P.S.: A privacy-preserving protocol for finding the nearest doctor in an emergency. In: PETRA 2010, pp. 18:1–18:8. ACM, New York (2010)

    Google Scholar 

  8. Du, W., Atallah, M.: Privacy-preserving cooperative statistical analysis. In: ACSAC 2001, pp. 102–112. IEEE, Los Alamitos (2001)

    Google Scholar 

  9. Du, W., Chen, S., Han, Y.S.: Privacy-preserving multivariate statistical analysis: Linear regression and classification. In: SDM 2004, pp. 222–233 (2004)

    Google Scholar 

  10. Duan, Y., Youdao, N., Canny, J., Zhan, J.Z.: P4P: practical large-scale privacy-preserving distributed computation robust against malicious users. In: USENIX Security Symposium, pp. 207–222 (2010)

    Google Scholar 

  11. Durresi, A., Durresi, M., Barolli, L.: Secure ubiquitous health monitoring system. In: Takizawa, M., Barolli, L., Enokido, T. (eds.) NBiS 2008. LNCS, vol. 5186, pp. 273–282. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  12. Dwork, C.: Differential privacy: a survey of results. In: Agrawal, M., Du, D.-Z., Duan, Z., Li, A. (eds.) TAMC 2008. LNCS, vol. 4978, pp. 1–19. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  13. Dwork, C., McSherry, F., Nissim, K., Smith, A.: Calibrating noise to sensitivity in private data analysis. In: Halevi, S., Rabin, T. (eds.) TCC 2006. LNCS, vol. 3876, pp. 265–284. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  14. Efraimidis, P.S., Drosatos, G., Nalbadis, F., Tasidou, A.: Towards privacy in personal data management. J. IMCS 17(4), 311–329 (2009)

    Google Scholar 

  15. Kantarcioglu, M., Kardes, O.: Privacy-preserving data mining in the malicious model. Int. J. IJICS 2(4), 353–375 (2008)

    Article  Google Scholar 

  16. Muntés-Mulero, V., Nin, J.: Privacy and anonymization for very large datasets. In: CIKM 2009, pp. 2117–2118. ACM, New York (2009)

    Google Scholar 

  17. Otto, C., Milenkovic, A., Sanders, C., Jovanov, E.: System Architecture of a Wireless Body Area Sensor Network for Ubiquitous Health Monitoring. J. JMM 1, 307–326 (2006)

    Google Scholar 

  18. Paillier, P.: Public-key cryptosystems based on composite degree residuosity classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  19. Yamazaki, A., Koyama, A., Arai, J., Barolli, L.: Design and implementation of a ubiquitous health monitoring system. Int. J. Web Grid Serv. 5, 339–355 (2009)

    Article  Google Scholar 

  20. Yao, A.C.C.: Protocols for secure computations (extended abstract). In: FOCS 1982, pp. 160–164. IEEE, Los Alamitos (1982)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Drosatos, G., Efraimidis, P.S. (2011). Privacy-Preserving Statistical Analysis on Ubiquitous Health Data. In: Furnell, S., Lambrinoudakis, C., Pernul, G. (eds) Trust, Privacy and Security in Digital Business. TrustBus 2011. Lecture Notes in Computer Science, vol 6863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22890-2_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22890-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22889-6

  • Online ISBN: 978-3-642-22890-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics