Resilient Security of Medical Cyber-Physical Systems

  • Aakarsh Rao
  • Nadir Carreón
  • Roman Lysecky
  • Jerzy Rozenblit
  • Johannes SametingerEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1062)


Incorporating network connectivity in cyber-physical systems (CPSs) leads to advances yielding better healthcare and quality of life for patients. However, such advances come with the risk of increased exposure to security vulnerabilities, threats, and attacks. Numerous vulnerabilities and potential attacks on these systems have been demonstrated. We posit that cyber-physical system software has to be designed and developed with security as a key consideration by enforcing fail-safe modes, ensuring critical functionality and risk management. In this paper, we propose operating modes, risk models, and runtime threat estimation for automatic switching to fail-safe modes when a security threat or vulnerability has been detected.


Cyber-physical system Medical device Security 



This work has partially been supported by the LIT Secure and Correct Systems Lab funded by the State of Upper Austria.


  1. 1.
    Biro, M., Mashkoor, A., Sametinger, J., Seker, R. (eds.) Software safety and security risk mitigation in cyber-physical systems. IEEE Softw. 35(1), 24–29 (2018)Google Scholar
  2. 2.
    Blyth, A., Thomas, P.: Performing real-time threat assessment of security incidents using data fusion of IDS logs. J. Comput. Secur. 14(6), 513–534 (2006)CrossRefGoogle Scholar
  3. 3.
    Krishnamurthy, R., Sastry, A., Balakrishnan, B.: How the internet of things is transforming medical devices. Cognizant 20–20 Insights, Cognizant (2016)Google Scholar
  4. 4.
    Li, C., Raghunathan, A., Jha, N.K.: Improving the trustworthiness of medical device software with formal verification methods. IEEE Embed. Syst. Lett. 5, 50–53 (2013)CrossRefGoogle Scholar
  5. 5.
    Lu, S., Seo, M., Lysecky, R.: Timing-based anomaly detection in embedded systems. In: Proceedings of the 20th Asia and South Pacific Design Automation Conference, pp. 809–814 (2015)Google Scholar
  6. 6.
    Lu, S., Lysecky, R.: Time and sequence integrated runtime anomaly detection for embedded systems. ACM Trans. Embed. Comput. Syst. 17(2), 38:1–38:27 (2018)Google Scholar
  7. 7.
    National Institute of Standards and Technology: Guide for Conducting Risk Assessments. NIST Special Publication 800–30 Revision 1, September 2012Google Scholar
  8. 8.
    Phan, L.T.X., Lee, I.: Towards a compositional multi-modal framework for adaptive cyber-physical systems. In: IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, pp. 67–73 (2011)Google Scholar
  9. 9.
    Phan, L.T.X., Chakraborty, S., Lee, I.: Timing analysis of mixed time/event-triggered multi-mode systems. In: IEEE Real-Time Systems Symposium (RTSS), pp. 271–280 (2009)Google Scholar
  10. 10.
    Rao, A., Rozenblit, J., Lysecky, R., Sametinger, J.: Composite risk modeling for automated threat mitigation in medical devices. In: Proceedings of the Modeling and Simulation in Medicine Symposium, Virginia Beach, VA, USA, pp. 899–908 (2017)Google Scholar
  11. 11.
    Rao, A., Carreon Rascon, N., Lysecky, R., Rozenblit, J.W.: Probabilistic security threat detection for risk management in cyber-physical medical systems. IEEE Softw. 35(1), 38–43 (2018)CrossRefGoogle Scholar
  12. 12.
    Rao, A., Rozenblit, J., Lysecky, R., Sametinger, J.: Trustworthy multi-modal framework for life-critical systems security. In: Annual Simulation Symposium, article no. 17, pp. 1–9 (2018)Google Scholar
  13. 13.
    Roberts, P.: Intel: New Approach Needed to Secure Connected Health Devices (2015).
  14. 14.
    Rose, K., Eldridge, S., Chapin, L.: The Internet of Things (IoT): An Overview-Understanding the Issues and Challenges of a More Connected World. Internet Society (2015)Google Scholar
  15. 15.
    Rostami, M., Juels, A., Koushanfar, F.: Heart-to-Heart (H2H): authentication for implanted medical devices. In: ACM SIGSAC Conference on Computer & Communications Security, pp. 1099–1112 (2013)Google Scholar
  16. 16.
    Sametinger, J., Steinwender, C.: Resilient context-aware medical device security. In: International Conference on Computational Science and Computational Intelligence, Symposium on Health Informatics and Medical Systems (CSCI-ISHI), Las Vegas, NV, USA, pp. 1775–1778 (2017)Google Scholar
  17. 17.
    Sametinger, J., Rozenblit, J., Lysecky, R., Ott, P.: Security challenges for medical devices. Commun. ACM 58(4), 74–82 (2015)CrossRefGoogle Scholar
  18. 18.
    Sametinger, J., Rozenblit, J.W.: Security scores for medical devices. In: Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 5: HEALTHINF, pp. 533–541 (2016)Google Scholar
  19. 19.
    Xu, F., Qin, Z., Tan, C.C., Wang, B., Li, Q.: IMDGuard: securing implantable medical devices with the external wearable guardian. In: IEEE INFOCOM (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Aakarsh Rao
    • 1
  • Nadir Carreón
    • 1
  • Roman Lysecky
    • 1
  • Jerzy Rozenblit
    • 1
  • Johannes Sametinger
    • 2
    Email author
  1. 1.University of ArizonaTucsonUSA
  2. 2.Johannes Kepler University LinzLinzAustria

Personalised recommendations