ENHANCED IOT SYSTEM SECURITY THROUGH ARTIFICIAL INTELLIGENCE

Abstract

The Internet of Things (IoT) transformed industries by enabling seamless device connectivity, but it also brought serious security risks like data breaches and illegal access. Traditional security measures can't keep up with the growth and evolution of IoT networks, which emphasises the need for more sophisticated solutions. By providing adaptive, real-time threat detection, anomaly identification, and automated defences against cyberattacks, integrating artificial intelligence (AI) into Internet of Things (IoT) systems has become a viable way to increase security. First, techniques like machine learning and deep learning use vast volumes of data to identify anomalous patterns and behaviours that enable prompt identification of suspicious threats. Hence, AI-based systems can be useful for improving Intrusion Detection Systems (IDS), optimizing security protocols, better protection against unauthorized access, and help minimize the risk of cyber-attacks. What is more, AI helps with predictive analytics, which enables IoT networks to predict and solve risks before they become real. With AI integration, IoT systems can even implement self-healing mechanisms to automatically recover from attacks. However, challenges such as computational power and data privacy, AI uses significantly improve IoT security offering a more flexible, undetected, and much more durable defence against impending threats. Organisations can secure and preserve the dependability and safety of their network of devices in the face of an increasingly complex cyber threat landscape by integrating AI with IoT.