LEVERAGING AI FOR ADVANCED THREAT DETECTION: MITIGATING ZERO-DAY ATTACKS IN HEALTHCARE SOFTWARE SYSTEMS
Frank Mensah · International Journal of Novel Research and Development · 2023
The digitization of healthcare systems has escalated the risk of sophisticated cyber threats, with zero-day attacks emerging as one of the most critical security concerns. These attacks exploit unknown vulnerabilities, rendering traditional security mechanisms inadequate. This paper critically explores the transformative role of Artificial Intelligence (AI) in detecting and mitigating zero-day threats within healthcare software systems. It evaluates AI-driven models—including supervised, unsupervised, and deep learning approaches—focusing on their effectiveness, adaptability, and operational challenges. The analysis not only highlights the superior performance of AI systems in threat detection but also interrogates their limitations in terms of explainability, resource demands, and ethical concerns. The study concludes with practical recommendations for healthcare stakeholders to implement robust, scalable, and transparent AI-based defense mechanisms, while also identifying pressing research gaps in regulatory frameworks and model bias mitigation.