Artificial Intelligence for Cybersecurity in Healthcare Systems: A Simple Review of Applications, Challenges, and Future Directions

Abstract

There is increased implementation of digital systems in healthcare. Medical centers accumulate a considerable amount of patient information in database systems and computers. This data is sensitive. Hackers can steal or destroy it. Cybersecurity is, therefore, extremely critical in healthcare. Healthcare systems may be made safer with the help of Artificial Intelligence (AI). Threats can be detected, attacks averted and rapid response provided by AI. Machine learning, deep learning, and anomaly detection are some of the AI techniques. The AI can be used to secure patient records, hospitals networks and medical devices. AI also has challenges. Patient information confidentiality is a major issue. AI may lack adequate good data in hospitals. AI systems are subject to attack by hackers. Using AI can be costly. Legal and ethical issues, such as patient consent, are also present. AI can also ensure the security and power of healthcare in the future. It can be assisted by new AI technologies, superior systems, and clear policies. This review examines the AI applications in healthcare cybersecurity, issues it experiences, and future actions.

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