Securing IoT using AI

Abstract

AI-driven security systems for IoT networks utilize advanced artificial intelligence (AI) technologies to monitor and manage connected devices in order to mitigate malicious activities which can disrupt network operations. Anomaly detection methods are used to identify traffic patterns or behaviors which show signs of suspicious activities, while learning adaptation allows the system to adjust parameters according to the threats faced. In addition, self-learning algorithms are employed to recognize patterns of IoT traffic and isolate any malicious activities which could lead to possible attacks. By leveraging machine learning capabilities, AI-driven security systems improve the security of connected devices, enabling them to respond quickly to threats and minimize any possible damage. In summary, AI-driven security for IoT systems is used to enhance the resilience of connected devices against cyber threats and protect them from malicious attacks more efficiently than traditional methods.