A Dynamic Distributed Architecture for Preserving Privacy of Medical IoT Monitoring Measurements

  • Salaheddin DarwishEmail author
  • Ilia Nouretdinov
  • Stephen Wolthusen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10898)


Medical and general health-related measurements can increasingly be performed via IoT components and protocols, whilst inexpensive sensors allow the capturing of a wider range of parameters in clinical, care, and general health monitoring domains. Measurements must typically be combined to allow e.g. differential diagnosis, and in many cases it is highly desirable to track progression over time or to detect anomalies in care and general monitoring contexts. However, the sensitive nature of such data requires safeguarding, particularly where data is retained by different third parties such as medical device manufacturers for extended periods. This appears to be very challenging especially when standards-based interoperability (i.e using IoT standards like HyperCAT or Web of Things-WoT) is to be achieved. This is because open meta-data of those standards can facilitate inference and source linkage if compiled or analysed by adversaries. Therefore, we propose an architecture of pseudonimyised distributed storage including a dynamic query analyser to protect the privacy of information being released.


Medical IoT Differential privacy Pseudonymisation Meta-data Anonymisation 



This work was supported by Technology Integrated Health Management (TIHM) project awarded to the School of Mathematics and Information Security at Royal Holloway as part of an initiative by NHS England supported by InnovateUK.


  1. 1.
    HealthKit — Apple Developer Documentation.
  2. 2.
  3. 3.
    Aamot, H., Kohl, C.D., Richter, D., Knaup-Gregori, P.: Pseudonymization of patient identifiers for translational research. BMC Med. Inform. Decis. Mak. 13(1), 75 (2013)CrossRefGoogle Scholar
  4. 4.
    Beart, P., Jaffey, T., Davies, J.: Hypercat 3.00 Specification (2016).
  5. 5.
    O’Keefe, C.M.: Protecting confidentiality while making data available for research and policy analysis.
  6. 6.
    Dalenius, T., Reiss, S.P.: Data-swapping: a technique for disclosure control. J. Stat. Plan. Inference 6(1), 73–85 (1982)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Dimitrov, D.V.: Medical internet of things and big data in healthcare. Healthc. Inf. Res. 22(3), 156–163 (2016)CrossRefGoogle Scholar
  8. 8.
    Duncan, G.: Statistical confidentiality: Is synthetic data the answer? (2006)., in UCLA IDRE:UCLA
  9. 9.
    Dwork, C., Roth, A.: The algorithmic foundations of differential privacy. Found. Trends Theor. Comput. Sci. 9(3/4), 211–407 (2014)MathSciNetzbMATHGoogle Scholar
  10. 10.
    El Emam, K., Jonker, E., Arbuckle, L., Malin, B.: A systematic review of re-identification attacks on health data. PLOS One 6(12), 1–12 (2011). Correction published in PLOS ONE 10(4)e0126772Google Scholar
  11. 11.
    Garfinkel, S.L.: NISTIR 8053. de-identification of personal information. Technical report, National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA (2015)Google Scholar
  12. 12.
  13. 13.
    Lin, Z., Hewett, M., Altman, R.B.: Using binning to maintain confidentiality of medical data. In: Proceedings of the AMIA Symposium, pp. 454–458 (2002)Google Scholar
  14. 14.
    Liu, C., Chakraborty, S., Mittal, P.: Dependence makes you vulnerable: differential privacy under dependent tuples. In: Network and Distributed System Security Symposium (2016)Google Scholar
  15. 15.
    Madaan, N., Ahad, M.A., Sastry, S.M.: Data integration in IoT ecosystem: Information linkage as a privacy threat. Computer Law & Security Review (2017)Google Scholar
  16. 16.
    Hadian, M., Liang, X., Altuwaiyan, T., Mahmoud, M.M.E.A.: Privacy-Preserving mHealth data release with pattern consistency. In: IEEE Global Communications Conference, pp. 1–6 (2016)Google Scholar
  17. 17.
    Narayanan, A., Shmatikov, V.: Myths and fallacies of “Personally Identifiable Information”. Commun. ACM 53(6), 24–26 (2010)CrossRefGoogle Scholar
  18. 18.
    Neubauer, T., Kolb, M.: An evaluation of technologies for the pseudonymization of medical data. Stud. Comput. Intell. 208, 47–60 (2009)Google Scholar
  19. 19.
    NOMINET: Privacy guidelines for IoT: what you need to know.
  20. 20.
    Paré, G., Moqadem, K., Pineau, G., St-Hilaire, C.: Clinical effects of home telemonitoring in the context of diabetes, asthma, heart failure and hypertension: a systematic review. J. Med. Internet Res. 12(2), e21 (2010)CrossRefGoogle Scholar
  21. 21.
    Rahmani, A.M., Gia, T.N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., Liljeberg, P.: Exploiting smart e-Health gateways at the edge of healthcare internet-of-things: a fog computing approach. Future Gener. Comput. Syst. 78(2), 641–658 (2018)CrossRefGoogle Scholar
  22. 22.
    Reiter, J.: Simultaneous use of multiple imputation for missing data and disclosure limitation. Survey Methodol. 30, 235–242 (2004)Google Scholar
  23. 23.
    Riazul Islam, S.M., Kwak, D., Kabir, H., Hossain, M., Kwak, K.-S.: A comprehensive survey. IEEE Access 3, 678–708 (2015)CrossRefGoogle Scholar
  24. 24.
    Selander, G., Mani, M., Kumar, S.: RFC 7744 - Use Cases for Authentication and Authorization in Constrained Environments. Technical report, Internet Engineering Task Force (IETF), May 2016.
  25. 25.
    Sweeney, L., Samarati, P.: Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. Harvard Data Privacy Lab (1998)Google Scholar
  26. 26.
    Tarouco, L.M.R., Bertholdo, L.M., Granville, L.Z., Arbiza, L.M.R., Carbone, F., Marotta, M., de Santanna, J.J.C.: Internet of Things in healthcare: interoperatibility and security issues. In: 2012 IEEE International Conference on Communication, pp. 6121–6125. IEEE, Junuary 2012Google Scholar
  27. 27.
    Ziegeldorf, J.H., Morchon, O.G., Wehrle, K.: Privacy in the internet of things: threats and challenges. Secur. Commun. Netw. 7(12), 2728–2742 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Salaheddin Darwish
    • 1
    Email author
  • Ilia Nouretdinov
    • 1
  • Stephen Wolthusen
    • 1
    • 2
  1. 1.School of Mathematics and Information SecurityRoyal Holloway, University of LondonEghamUK
  2. 2.Department of Information Security and Communication TechnologyNorwegian University of Science and TechnologyTrondheimNorway

Personalised recommendations