Privacy Protection for Point-of-Care Using Chaotic Maps-Based Authentication and Key Agreement.

Recently, remote points-of-care as a novel medical model has emerged and received considerable attention due to its convenient medical services such as efficient real-time monitoring and prompt information feedback. Although the points-of-care has more attractive advantages compared with traditional health care systems, some important issues still require a serious consideration such as privacy protection and the security of the transmitted biomedical signals. In this study, we propose a novel authentication and key agreement mechanism that ensures privacy preservation and provides biomedical signals protection during the communication process by negotiating a shared key to encrypt/decrypt sensitive information. Chaotic maps are employed in our design to achieve mutual authentication and key agreement for resource-constrained points-of-care, which also increases the efficiency in comparison with those schemes designed by Elliptic Curve Cryptography or RSA. Furthermore, dynamic identities are adopted in the proposed scheme to achieve user anonymity and user untraceability for the high-privacy-required points-of-care. The security of the proposed scheme is proven via Real-or-Random model. The performance analysis shows that the proposed scheme reduces computational overhead in comparison with the state-of-the-art schemes.