An Anonymous Authentication Protocol Based on Cloud for Telemedical Systems

Abstract

Telecare medical information systems (TMIS) enable patients to access healthcare delivery services conveniently. With the explosive development occurring in cloud computing and services, storage of personal medical and health information outsourcing to cloud infrastructure has been a potential alternative. However, this has entailed many considerable security and privacy issues. In order to address the security loopholes, we propose a promising solution satisfying the requirements of cloud computing scenarios for telemedical systems. The proposed scheme could provide both data confidentiality and message authenticity while preserving anonymity. Furthermore, the formal security proof demonstrates that the proposed scheme is resistant to various attacks. The performance comparisons show the proposal’s workability and it is well suited to adoption in telemedical services.

A Secured and Efficient Anonymous Roaming Scheme of Mobile Internet

“…To ensure the legitimacy of MT identity, for example, in [1], an anonymous identity authentication and key agreement scheme for global mobility network is proposed to realize mutual anonymous authentication between the two parties. In [2], a wireless anonymous authentication protocol is proposed to avoid the risk of using the same key for a long time. In [3], an identity-based anonymous wireless authentication scheme is proposed to solve the authentication problem of mobile users while roaming, and the security and anonymity of the scheme are analyzed in detail by using the characteristics of bilinear pairs and elliptic curves.…”

“…However, the partial roaming authentication protocol [1,2] only completes the authentication between the authentication server and the MT for local communication. When MT roams away from the local network to enter the remote network, two-way anonymous authentication between MT and remote network authentication server cannot be realized.…”

A Secure and Verifiable Outsourcing Scheme for Assisting Mobile Device Training Machine Learning Model

“…Therefore, outsourcing data to the cloud has become the choice of many users, but it also brings security and privacy risks. Therefore, Li et al [12] proposed an anonymous authorization scheme to ensure the confidentiality and authenticity of the data. Ding et al [13] studied the data access control scheme under ciphertext, which can also perform effective calculations while ensuring flexible access control.…”

“…Ding et al [13] studied the data access control scheme under ciphertext, which can also perform effective calculations while ensuring flexible access control. Similarly, when applying edge computing to model training for local devices and nodes, data security and privacy issues cannot be ignored [12,14,15]. For example, in the application scenarios of user data collection such as smart medical devices and smart bracelets, the local device continuously accesses the user's geographic location, physical characteristics (including heart rate, stride, voiceprint, and other characteristics), or medical characteristics, which is apart from the collection and processing data by these devices that include a large number of user's privacy characteristics.…”