Privacy-preserving and Secure Health Data Management for Epidemics: A Cryptographic Approach

The global health community faces unprecedented challenges from emerging infectious diseases, necessitating robust information management systems to ensure timely and effective public health responses. This paper addresses the critical need for secure and efficient health data management during epidemics by proposing a novel framework that integrates advanced cryptographic techniques. The framework leverages the Elliptic Curve German Digital Signature Algorithm (ECGDSA) for data authenticity and integrity, the Elliptic Curve Integrated Encryption Scheme (ECIES) for secure data transmission, and Paillier Homomorphic Encryption for privacy-preserving data aggregation. These techniques enable secure communication and data sharing among Laboratories (LABs), City Health Centers (CHCs), and the Ministry of Health and Treatment (MHT), even in resource-constrained environments. The proposed system is designed to be scalable and flexible, making it applicable across various administrative levels, from local to global. We validate its security and correctness through group-theoretic analysis and formal verification with Proverif. Performance evaluations reveal the framework's computational advantage over blockchain methods, which incur higher consensus overhead despite offering decentralization, and further highlight ECGDSA's superior signing efficiency compared to the Elliptic Curve Digital Signature Algorithm (ECDSA). This framework safeguards sensitive health data, enhances epidemic response with timely insights, and provides a comprehensive, secure solution for managing health information in an interconnected world facing evolving disease threats.