The expanded connectivity results from adding more IoT devices between healthcare systems and smart homes, as well as industrial automation and transportation networks.Cybercriminals target multiple IoT devices because these devices face numerous dangerous security threats on their networks.Present security solutions for IoT networks demonstrate inadequacy because they primarily focus on limited resources despite the requirement for specific configuration procedures among IoT devices.Security tools equipped with AI enable IoT networks to track forthcoming threats, which automatically trigger security protocols to activate predefined security modification procedures.Research findings demonstrate how integration between artificial intelligence functionality with metadata elements creates exceptionally secure network security systems for combating escalating IoT network threats.IoT network security defense works best when security measures interlace with AI technology to stop present and future-facing cybersecurity threats.The analysis of substantial data volumes by advanced AI systems uses gathered data to detect prospective hacker system breaches.The implementation of security-specific machine learning algorithms leads to automatic defense measures that both detect various cyberattacks and activate safeguard mechanisms.The security defenses of protection systems improve with artificial intelligence-based learning algorithms that identify new network environments.
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