A Systematic Literature Review of the Emerging Technologies used in Securing Healthcare Data

This study investigates the unification of blockchain technology and artificial intelligence (AI) models to improve the security and privacy of healthcare records. As healthcare systems increasingly depend on digital technologies, the protection of sensitive patient information has become a critical challenge. Blockchain's decentralized, immutable ledger offers robust data integrity and transparency, while AI techniques provide powerful tools for predictive analytics and decision-making. However, combining these two technologies introduces substantial challenges, including scalability issues, privacy concerns, and the requirement for regulatory compliance. This study systematically reviews existing literature to identify key challenges and promise solutions in the amalgamation of blockchain and AI within healthcare. We evaluate the applicability, objectives, techniques, and security measures of selected studies to assess their relevance and contribution to the field. Our findings reveal that while significant progress has been made, gaps remain in areas such as the alignment of these technologies with regulatory frameworks, the development of privacy-preserving AI methods, and the protection of AI models from adversarial attacks. The paper concludes by proposing a set of research questions and future directions to address these challenges, with the aim of advancing the secure and ethical integration of blockchain and AI in healthcare.