AI-powered cloud security for IoT: Using generative AI for secure IoT device authentication and communication
Rahul Vadisetty, Anand Polamarasetti · 2026
The rapid proliferation of IoT devices vastly expanded connectivity in many industries and simultaneously introduced several security vulnerabilities. Traditional methods of IoT security cannot meet the demands brought about by real-time protection and scalability required due to diverse IoT ecosystems. The application of cloud-based artificial intelligence, incredibly generative AI, can be one of the promising ways to overcome these difficulties. This research aims to discuss generative AI for the authentication and communication of IoT devices securely. It comes up with AI-driven approaches towards improving security in cloud environments. Generative AI, referring to GANs, can simulate threats dynamically, generate cryptographic keys, and change their authentication protocols to counteract the breach. The generative AI can provide anomaly detection, monitor communication channels in real-time for any possible interception of data, and ensure that a security standard of encryption is met. This work is also intended to discuss scaling generative AI models by cloud platforms, which are set to enable efficient processing and flexible deployment across IoT networks with ease. The research addresses data privacy, ethical considerations, and compliance challenges associated with deploying generative AI in cloud-integrated IoT systems. The findings indicate that generative AI will revolutionize IoT Security by providing scalable, adaptive, and highly automated security solutions that offer wide avenues for future research in secure, cloud-based ecosystems of IoT.