Integrating AI, Quantum Computing, and Blockchain for Secure Healthcare Data Management Addressing Regulatory and Implementation Challenges
Arafat Ashrafi Talha, Maruf Farhan · 2025
This chapter explores the integration of AI, quantum computing, and blockchain to enhance the security of electronic health records (EHR) in healthcare. The proposed model combines AI-driven analytics with quantum computing to improve the performance of security information and event management (SIEM) and security orchestration, automation, and response (SOAR) systems. These advancements enable real-time threat detection, efficient data processing, and reduced latency. Additionally, blockchain networks provide a decentralized, immutable ledger for secure EHR transactions, ensuring data confidentiality, integrity, and availability. The model also incorporates a decentralized storage system to safeguard data against unauthorized access, while maintaining efficient access for authorized users through hospital management systems. By integrating these technologies, the model offers a comprehensive solution to healthcare data security, addressing key concerns around privacy, data integrity, and regulatory compliance. The chapter also discusses the challenges associated with implementing such a system, including interoperability and scalability issues as well as the need for continued research and development to ensure effective deployment in real-world healthcare environments. This approach presents a promising framework for enhancing healthcare data security, providing healthcare organizations with a robust toolset to manage sensitive information securely.