AI-Powered Security for Internet of Medical Things (IoMT) Devices

Abstract

The rapid proliferation of Internet of Medical Things (IoMT) devices has transformed healthcare delivery by enabling real-time monitoring, remote diagnostics, and improved patient outcomes. However, this interconnected landscape also introduces significant cybersecurity challenges, as the increasing number of IoMT devices presents a larger attack surface for potential cyber threats. This paper examines how artificial intelligence (AI) enhances the security of IoMT devices, focusing on its ability to prevent cyberattacks and ensure patient safety and data privacy. By leveraging machine learning algorithms, anomaly detection techniques, and predictive analytics, AI can proactively identify and mitigate vulnerabilities in IoMT networks. Furthermore, AI-driven security frameworks enable continuous monitoring and adaptive responses to emerging threats, thereby bolstering the resilience of medical devices against cyberattacks. This paper also discusses the ethical considerations and regulatory implications associated with the integration of AI in IoMT security, highlighting the need for robust security protocols and compliance with healthcare regulations. Ultimately, this study underscores the critical role of AI in safeguarding the integrity of IoMT ecosystems, ensuring that patient safety and data privacy remain paramount in an increasingly digital healthcare environment.