Abstract

AI in healthcare data security is a significant development since healthcare is progressively leaning towards electronic health records, telemedicine, and mobile health apps. These technologies have greatly enhanced the quality of patient care and operation efficiency. However, at the same time, they have also assumed considerable hazards by opening up patients' information to cybercriminals. It is also noteworthy that healthcare organizations are especially attractive to hackers since they work with personal, financial, and medical data. While initial levels of cyber defense include firewall security systems, encryption security, and user access controls, they are no longer sufficient to combat today's advanced cyber threats, including ransomware, phishing, APTs, etc.

Drawing on the literature, this paper explores the importance of AI in protecting healthcare data while describing its strengths in real-time threat detection, anomaly prediction, and incident response. The AI system can analyze and make decisions for those large sums of data much faster and even more efficiently for detecting and responding to threats in the organization's healthcare than the traditional methodologies. Besides, AI enhances security by applying advanced encryption, data anonymization, and compliance with regulatory requirements, making healthcare's sensitive data more secure, accurate, and accessible while it remains protected.

However, the introduction of AI in healthcare data security has some complications. Privacy constraints for patients, potential issues with biased algorithms, high cost of integration, and adversarial attacks on algorithms are some of the greatest challenges of implementing AI (Mennella et al., 2024). Still, the future of AI in healthcare data security has great potential. New-generation technologies such as federated learning, quantum-resistant encryption, and threat intelligence sharing using AI are believed to have tremendous potential in the industry.

Thus, utilizing AI tools in healthcare is an active, effective, challenging-responsive tendency, which, now and in the future, will successfully cope with the problem of health data security. When implemented and integrated appropriately, these artificial intelligence technologies make healthcare organizations more secure from hacking threats, save compliance with the new standards in the healthcare system, and thus protect patients' confidence, which is all significant towards making the healthcare experience better for patients.

This work is licensed under a Creative Commons Attribution 4.0 License.