AI-DRIVEN CYBERSECURITY FOR IOT DEVICES

Abstract

The pervasive proliferation of Internet of Things (IoT) devices has ushered in an era of unprecedented connectivity and convenience, yet simultaneously unveiled a vast, complex, and vulnerable attack surface. Traditional, signature-based cybersecurity paradigms have proven largely insufficient against the dynamic, diverse, and often resource-constrained nature of IoT ecosystems. This article critically examines the imperative for and application of AI-driven cybersecurity solutions to fortify IoT devices. It delves into the inherent vulnerabilities of IoT, highlights the shortcomings of conventional security measures, and systematically explores core AI and machine learning paradigms pertinent to threat detection and mitigation. Practical applications across various security domains are discussed, alongside a candid assessment of the challenges, limitations, and ethical considerations inherent in deploying AI for IoT security. The article concludes by charting future research directions and advocating for a holistic, collaborative approach to ensure the resilient protection of the expanding IoT landscape.