Design A Cryptosystem Based Healthcare Cyber Security Model, Contributing With Key Distribution For Different Attack

Abstract

The rapid digitalization of healthcare systems has significantly improved the efficiency of medical services, patient record management, and remote healthcare delivery. However, the increasing reliance on interconnected healthcare networks has also exposed sensitive patient information to various cybersecurity threats, including eavesdropping, replay attacks, man-in-the-middle attacks, data breaches, and unauthorized access. Ensuring the confidentiality, integrity, and availability of healthcare data has therefore become a critical requirement for modern healthcare infrastructures. This research proposes a cryptosystem-based healthcare cybersecurity model that integrates advanced cryptographic techniques with a secure and dynamic key distribution mechanism to protect sensitive medical information during both transmission and storage. The proposed model combines symmetric encryption and asymmetric encryption to leverage the advantages of both approaches. Symmetric encryption is utilized for efficient and high-speed data encryption, while asymmetric encryption facilitates secure key exchange and authentication among healthcare entities such as patients, doctors, hospitals, and cloud servers. A dynamic key distribution framework is incorporated to generate, distribute, and periodically refresh session keys, thereby enhancing resistance against cyberattacks including replay attacks, eavesdropping, key compromise, and man-in-the-middle attacks. Additionally, secure authentication mechanisms and integrity verification techniques are employed to ensure that only authorized users can access healthcare data and that transmitted information remains unaltered. To evaluate the effectiveness of the proposed model, simulations are conducted under various attack scenarios commonly encountered in healthcare environments. Performance metrics such as encryption and decryption time, key generation efficiency, attack detection rate, computational overhead, scalability, and security resilience are analyzed. The results are expected to demonstrate that the proposed cryptosystem provides strong protection against multiple cyber threats while maintaining efficient communication and data processing capabilities. Furthermore, the framework is designed to be practical, scalable, and compatible with existing healthcare information systems, enabling seamless integration without significant infrastructure modifications. By enhancing healthcare data security through advanced cryptographic techniques and secure key management, the proposed model contributes to the protection of patient privacy, secure healthcare communication, and regulatory compliance with standards such as the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR). The research aims to provide a comprehensive and reliable cybersecurity solution capable of addressing emerging security challenges in modern healthcare ecosystems.