A lightweight and robust authentication scheme for the healthcare system using public cloud server.

Area of Science:

• Computer Science
• Information Security
• Healthcare Technology

Background:

• Public cloud servers face significant security threats, particularly in sensitive sectors like healthcare, risking patient data privacy.
• Existing security protocols for cloud-enabled healthcare systems often lack efficiency or are vulnerable to attacks like replay attacks.
• Balancing robust security with performance in cloud healthcare systems remains a critical challenge.

Purpose of the Study:

• To propose a novel, robust security method for cloud-enabled healthcare systems.
• To enhance the security and privacy of sensitive patient data in cloud environments.
• To improve the efficiency of security protocols in terms of communication and computation costs.

Main Methods:

• Development of a security scheme integrating fuzzy extractors with Elliptic Curve Cryptography (ECC).
• Formal security analysis using BAN logic, Random Oracle Model (ROM), and ProVerif.
• Informal security validation through pragmatic illustrations and discussion of potential attacks.
• Comparative analysis of communication and computation costs against existing protocols.

Main Results:

• The proposed scheme demonstrates enhanced security and privacy for cloud-enabled healthcare systems.
• Formal and informal analyses confirm the robustness of the security mechanism.
• Achieved a 33.91% reduction in communication costs and a 35.39% improvement in computation costs compared to prior methods.

Conclusions:

• The proposed ECC-based fuzzy extractor method offers a superior security solution for cloud healthcare.
• The scheme effectively balances security requirements with performance efficiency.
• This work provides a significant advancement in securing cloud-based healthcare services.