Abstract

The heightened digitization of the healthcare industry has led to an exponential increase in sensitive patient data, which requires robust security models to prevent breaches, unauthorized access, and cyber attacks. Traditional security protocols are inadequate, and this has made it imperative to explore Artificial Intelligence (AI) and Blockchain as novel solutions. AI enhances healthcare cybersecurity by facilitating real-time anomaly detection, predictive analysis, and automated threat response, while blockchain offers decentralization, immutability, and secure data sharing. However, blockchain technology faces major challenges for scalability and performance, as represented by lengthy transaction processing durations and high storage demands, elements that could deter its widespread adoption across the healthcare industry. To help counter these challenges, researchers are exploring Layer 2 scaling solutions, hybrid blockchain architectures, and off-chain storage strategies. In addition, cleanroom technology provides a controlled and secure environment for handling sensitive healthcare data, protecting privacy while also supporting AI-driven analytics and research collaboration. This article critically examines the intersection of blockchain and AI for healthcare security, in terms of challenges, use cases, and direction. Leveraging these technologies, health organizations can set up future-proof models of security that address data integrity, regulatory requirements, and resistance to future threats more effectively