Wireless Networks

, Volume 25, Issue 8, pp 4737–4750 | Cite as

Authenticated key agreement scheme for fog-driven IoT healthcare system

  • Xiaoying Jia
  • Debiao HeEmail author
  • Neeraj Kumar
  • Kim-Kwang Raymond Choo


The convergence of cloud computing and Internet of Things (IoT) is partially due to the pragmatic need for delivering extended services to a broader user base in diverse situations. However, cloud computing has its limitation for applications requiring low-latency and high mobility, particularly in adversarial settings (e.g. battlefields). To some extent, such limitations can be mitigated in a fog computing paradigm since the latter bridges the gap between remote cloud data center and the end devices (via some fog nodes). However, fog nodes are often deployed in remote and unprotected places. This necessitates the design of security solutions for a fog-based environment. In this paper, we investigate the fog-driven IoT healthcare system, focusing only on authentication and key agreement. Specifically, we propose a three-party authenticated key agreement protocol from bilinear pairings. We introduce the security model and present the formal security proof, as well as security analysis against common attacks. We then evaluate its performance, in terms of communication and computation costs.


Fog computing Cloud computing Internet-of-Things (IoT) Healthcare Authenticated key agreement 



The work was supported in part by the National Natural Science Foundation of China (Nos. 61501333, 61572379, U1536204) and the National High-Tech Research and Development Program of China (863 Program) (No. 2015AA016004) and in part by the Fundamental Research Funds for the Central Universities under Grant CZY18034.


  1. 1.
    Alrawais, A., Alhothaily, A., Hu, C., & Cheng, X. (2017). Fog computing for the internet of things: Security and privacy issues. IEEE Internet Computing, 21(2), 34–42.CrossRefGoogle Scholar
  2. 2.
    Amin, R., Kumar, N., Biswas, G., Iqbal, R., & Chang, V. (2018). A light weight authentication protocol for iot-enabled devices in distributed cloud computing environment. Future Generation Computer Systems, 78, 1005–1019.CrossRefGoogle Scholar
  3. 3.
    Bellare, M., Pointcheval, D., & Rogaway, P. (2000). Authenticated key exchange secure against dictionary attacks. Tecnologia Electronica E Informatica, 1807, 139–155.zbMATHGoogle Scholar
  4. 4.
    Bonomi, F., Milito, R., Natarajan, P., & Zhu, J. (2014). Fog computing: A platform for internet of things and analytics. In Big data and internet of things: A roadmap for smart environments (pp. 169–186). Cham: Springer.Google Scholar
  5. 5.
    Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012, August). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing (pp. 13–16). ACM.Google Scholar
  6. 6.
    Chaudhry, S. A., Naqvi, H., Mahmood, K., Ahmad, H. F., & Khan, M. K. (2017). An improved remote user authentication scheme using elliptic curve cryptography. Wireless Personal Communications, 96(4), 5355–5373.CrossRefGoogle Scholar
  7. 7.
    Choo, K. K. R. (2009). Secure key establishment, advances in information security (Vol. 41). Berlin: Springer.CrossRefGoogle Scholar
  8. 8.
    Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., & Mankodiya, K. (2018). Towards fog-driven IoT ehealth: Promises and challenges of IoT in medicine and healthcare. Future Generation Computer Systems, 78, 659–676.CrossRefGoogle Scholar
  9. 9.
    Farash, M. S., Turkanović, M., Kumari, S., & Hölbl, M. (2016). An efficient user authentication and key agreement scheme for heterogeneous wireless sensor network tailored for the internet of things environment. Ad Hoc Networks, 36, 152–176.CrossRefGoogle Scholar
  10. 10.
    Gia, T. N., Jiang, M., Rahmani, A. M., Westerlund, T., Liljeberg, P., & Tenhunen, H. (2015, October). Fog computing in healthcare internet of things: A case study on ecg feature extraction. In IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM)  (pp. 356–363). IEEE.Google Scholar
  11. 11.
    Hamid, H. A. A., Rahman, S. M. M., Hossain, M. S., Almogren, A., & Alamri, A. (2017). A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access, 5, 22313–22328.CrossRefGoogle Scholar
  12. 12.
    Hayajneh, T., Mohd, B. J., Imran, M., Almashaqbeh, G., & Vasilakos, A. V. (2016). Secure authentication for remote patient monitoring with wireless medical sensor networks. Sensors, 16(4), 424.CrossRefGoogle Scholar
  13. 13.
    He, D., & Wang, D. (2015). Robust biometrics-based authentication scheme for multiserver environment. IEEE Systems Journal, 9(3), 816–823.CrossRefGoogle Scholar
  14. 14.
    Hu, P., Dhelim, S., Ning, H., & Qiu, T. (2017). Survey on fog computing: Architecture, key technologies, applications and open issues. Journal of Network & Computer Applications, 98, 27–42.CrossRefGoogle Scholar
  15. 15.
    Huang, C., Lu, R., & Choo, K. K. R. (2017). Vehicular fog computing: Architecture, use case, and security and forensic challenges. IEEE Communications Magazine, 55(11), 105–111.CrossRefGoogle Scholar
  16. 16.
    Joux, A. (2004). A one round protocol for tripartite diffie-hellman. Journal of Cryptology, 17(4), 263–276.CrossRefMathSciNetGoogle Scholar
  17. 17.
    Khan, S., Parkinson, S., & Qin, Y. (2017). Fog computing security: A review of current applications and security solutions. Journal of Cloud Computing, 6(1), 19.CrossRefGoogle Scholar
  18. 18.
    Kwon, J. O., Jeong, I. R., Sakurai, K., & Dong, H. L. (2007). Efficient verifier-based password-authenticated key exchange in the three-party setting. Computer Standards & Interfaces, 29(5), 513–520.CrossRefGoogle Scholar
  19. 19.
    Lee, T. F., Liu, J. L., Sung, M. J., Yang, S. B., & Chen, C. M. (2009). Communication-efficient three-party protocols for authentication and key agreement. Computers & Mathematics with Applications, 58(4), 641–648.CrossRefMathSciNetGoogle Scholar
  20. 20.
    Li, C. T., Wu, T. Y., Chen, C. L., Lee, C. C., & Chen, C. M. (2017). An efficient user authentication and user anonymity scheme with provably security for IoT-based medical care system. Sensors, 17(7), 1482.CrossRefGoogle Scholar
  21. 21.
    Liu, C. H., & Chung, Y. F. (2017). Secure user authentication scheme for wireless healthcare sensor networks. Computers & Electrical Engineering, 59, 250–261.CrossRefGoogle Scholar
  22. 22.
    Osanaiye, O. A., Chen, S., Zheng Yan, R. L., Choo, K. K. R., & Dlodlo, M. E. (2017). From cloud to fog computing: A review and a conceptual live vm migration framework. IEEE Access, 5, 8284–8300.CrossRefGoogle Scholar
  23. 23.
    Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., et al. (2018). Exploiting smart e-health gateways at the edge of healthcare internet-of-things: A fog computing approach. Future Generation Computer Systems, 78, 641–658.CrossRefGoogle Scholar
  24. 24.
    Sookhak, M., Yu, R., He, Y., Talebian, H., Safa, N. S., Zhao, N., et al. (2017). Fog vehicular computing: Augmentation of fog computing using vehicular cloud computing. IEEE Vehicular Technology Magazine, PP(99), 1–1.Google Scholar
  25. 25.
    Stojmenovic, I., & Wen, S. (2014, September). The fog computing paradigm: Scenarios and security issues. In Computer Science and Information Systems (FedCSIS), 2014 Federated Conference on (pp. 1–8). IEEE.Google Scholar
  26. 26.
    Stojmenovic, I., Wen, S., Huang, X., & Luan, H. (2016). An overview of fog computing and its security issues. Concurrency & Computation Practice & Experience, 28(10), 2991–3005.CrossRefGoogle Scholar
  27. 27.
    Turkanović, M., Brumen, B., & Hölbl, M. (2014). A novel user authentication and key agreement scheme for heterogeneous ad hoc wireless sensor networks, based on the internet of things notion. Ad Hoc Networks, 20, 96–112.CrossRefGoogle Scholar
  28. 28.
    Wang, D., & Wang, P. (2014). On the anonymity of two-factor authentication schemes for wireless sensor networks: Attacks, principle and solutions. Computer Networks, 73, 41–57.CrossRefGoogle Scholar
  29. 29.
    Xie, Q., Wong, D. S., Wang, G., Tan, X., Chen, K., & Fang, L. (2017). Provably secure dynamic id-based anonymous two-factor authenticated key exchange protocol with extended security model. IEEE Transactions on Information Forensics and Security, 12(6), 1382–1392.CrossRefGoogle Scholar
  30. 30.
    Yeh, H. L., Chen, T. H., Liu, P. C., Kim, T. H., & Wei, H. W. (2011). A secured authentication protocol for wireless sensor networks using elliptic curves cryptography. Sensors, 11(5), 4767–4779.CrossRefGoogle Scholar
  31. 31.
    Yi, S., Qin, Z., & Li, Q. (2015). Security and privacy issues of fog computing: A survey. In International conference on wireless algorithms, systems, and applications (pp. 685–695). Springer.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematics and StatisticsSouth-Central University for NationalitiesWuhanChina
  2. 2.Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education, School of Cyber Science and EngineeringWuhan UniversityWuhanChina
  3. 3.Department of Computer Science and EngineeringThapar UniversityPatialaIndia
  4. 4.Department of Information Systems and Cyber SecurityThe University of Texas at San AntonioSan AntonioUSA
  5. 5.Department of Electrical and Computer EngineeringThe University of Texas at San AntonioSan AntonioUSA

Personalised recommendations