As healthcare systems adopt advanced technologies like electronic health records, telemedicine, and wearable health devices, the volume of sensitive information grows, making it a target for cyberattacks. Artificial intelligence (AI) enhances security by offering real-time threat detection, anomaly identification, and adaptive defenses that can anticipate and counter cyber threats. AI plays a pivotal role in ensuring privacy by implementing advanced encryption techniques, access controls, and compliance monitoring, all while maintaining patient care. Further research of the integration of AI into healthcare cybersecurity strategies may assist organizations in strengthening their defenses, protecting patient confidentiality, and ensuring regulatory compliance in a digital landscape. AI-Driven Healthcare Cybersecurity and Privacy explores the integration of intelligent technologies into medical data security and privacy. It examines the role of AI in securing patients’ medical information, as well as organizational privacy techniques for broader healthcare systems. This book covers topics such as federated learning, deep learning, and cloud technology, and is a useful resource for engineers, computer and data scientists, security professionals, medical and healthcare workers, academicians, and researchers.