Leveraging Generative AI for Advanced Cybersecurity Enhancing Threat Detection and Mitigation in Healthcare Systems

The healthcare sector is increasingly reliant on interconnected systems and digital infrastructures, making it a prime target for sophisticated cyberattacks. These attacks threaten patient data, disrupt medical services, and pose serious financial and reputational risks. Traditional cybersecurity approaches, while effective to a degree, often struggle to detect and mitigate the rapidly evolving nature of threats in real-time. This paper explores the integration of Generative Artificial Intelligence (GenAI) into cybersecurity frameworks tailored for healthcare systems to address these challenges.Generative AI models, with their advanced capabilities in pattern recognition, anomaly detection, and predictive analysis, offer transformative potential in enhancing cybersecurity measures. Specifically, this study examines how GenAI can identify complex, multi-vector cyber threats by analyzing vast datasets, including network logs, user behavior, and system anomalies. By employing deep learning architectures such as Generative Adversarial Networks (GANs) and transformers, these models can simulate potential attack scenarios, anticipate adversarial tactics, and generate proactive defense mechanisms. Furthermore, the study investigates the use of GenAI in securing electronic health records (EHRs), safeguarding Internet of Medical Things (IoMT) devices, and fortifying telemedicine platforms. Special emphasis is placed on how these AI-driven solutions can detect ransomware, phishing attempts, and insider threats without compromising patient privacy or regulatory compliance. The implementation of GenAI also introduces challenges, such as the potential for adversarial misuse and computational overhead, which are critically analyzed. Through a series of case studies and experiments, this paper demonstrates the efficacy of GenAI in reducing false positives, improving response times, and mitigating real-world cyber threats within healthcare settings. The findings underscore the necessity of integrating GenAI into cybersecurity strategies to safeguard sensitive healthcare systems and ensure their resilience against emerging cyber threats. This research concludes with recommendations for policy makers, healthcare administrators, and technologists to adopt ethical, scalable, and robust AI-driven cybersecurity frameworks.