Gia, T. N., Jiang, M., Rahmani, A.M., Westerlund, T., Liljeberg, P., Tenhunen, H. (2015, October). Fog calculation on the Internet of Things in the health field: a case study on the extraction of ecg features. The IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; reliable, autonomous and safe computing Penetrating intelligence and data processing (CIT/IUCC/DASC/PICOM) (p. 356-363). ieee. Hamid, H. A.
A., Rahman, S.M.M., Hossain, M. S., Almogren, A., Alamri, A. (2017). A security model to preserve the privacy of medical big data in a healthcare cloud using a fog computing system using a coupling-based cryptography. IEEE Access, 5, 22313-22328. Jia, X., He, D., Kumar, N. et al. Authenticated key agreement system for the fog-controlled IoT health system. Wireless Netw 25, 4737-4750 (2019). doi.org/10.1007/s11276-018-1759-3 Li, C. T., Wu, T. Y., Chen, C.
L., Lee, C.C., Chen, C.M (2017). An effective user authentication and anonymity scheme with verifiable security for the IoT-based medical care system. Sensors, 17 (7), 1482. Add information about the works you`ve published. You can do this by importing other systems or by adding details manually. Read more Lee, T. F., Liu, J. L., Sung, M.
J., Yang, S.B., Chen, C.M. (2009). Effective three-year communication protocols for authentication and key agreement. Computer and mathematics with applications, 58 (4), 641-648. Chaudhry, S.A., Naqvi, H., Mahmood, K., Ahmad, H. F., Khan, M. K. (2017). An improved remote user authentication scheme with cryptography of elliptical curves. Personal wireless communication, 96 (4), 5355-5373. Rahmani, A.M., Gia, T.
N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., et al. (2018). Using smart e-health gateways on the margins of the Internet-Of-Things in the health field: an approach to calculating fog. Next-generation computer systems, 78, 641-658. Farash, M. S., Turkanovic, M., Kumari, S., ` Gulbl, M. (2016). Effective user authentication and a key tuning system for a heterogeneous wireless sensor network tailored to the Internet of Things. Ad hoc Networks, 36, 152-176. He, D., Wang, D. (2015). Robust biometric authentication system for multi-server environments.
IEEE Systems Journal, 9 (3), 816-823. The convergence between cloud computing and the Internet of Things (IoT) is partly due to the pragmatic need to provide broader services to a wider user base in different situations. However, cloud computing is limited to applications that require low latency and high mobility, especially in conflicting environments (for example. B battlefields). To some extent, such limitations can be mitigated in a fog calculation paradigm, as fog fills the gap between the remote cloud data center and the terminals (via a few fog nodes). However, fog knots are often used in isolated and unprotected areas. This requires the design of safety solutions for a fog-based environment. In this article, we look at the fog IoT health system that focuses solely on authentication and key agreement. In particular, we propose a tripartite key memorandum of understanding based on bi-speaking pairings.
We present the security model and present formal security evidence and security analysis against frequent attacks. We then evaluate performance in terms of communication and computational costs. Farahani, B., Firouzi, F., Chang, V., Badaroglu, M., Constant, N., Mankodiya, K. (2018). On the way to fog IoT: the promises and challenges of IoT in medicine and health. Next-generation computer systems, 78, 659-676. Wang, D., Wang, S. (2014).
On the anonymity of two-factor authentication schemes for wireless sensor networks: attacks, principle and solutions.