Secure and Efficient Authentication Scheme in IOT Environments based OT

The swift growth in the number of Internet of Things (IoT) devices and their deployment into Operational Technology (OT) settings has brought about difficult security issues, including authentication. Current procedures are deficient of scalability, theft of credentials and real-time dynamism, which expose the IoT-OT networks to threats. This paper will present a zero-trust authentication system that uses Artificial Intelligence (AI), blockchain, and Elliptic Curve Cryptography (ECC) to provide a decentralized, adaptive, and lightweight security system. The framework uses situational data, i.e. the location of a device, a history of behaviors, and access patterns to facilitate continuous identity checking without interrupting activities. AI actively identifies anomalies and prompt re-authentication, whereas blockchain allows managing identities transparently and without tampering by distributed devices. Lightweight ECC and XOR encryption are high security and low computation intensity algorithms that are used to overcome resource limitations. The 37 percent reduction in encryption time, 41 percent decreased energy usage and six-fold minimization of error rate over the traditional ECC techniques is shown by simulation and formal verification with ProVerif. The results verify the ability of the proposed approach to increase trust, performance, and resilience in industrial IoT-OT systems. This study makes a theoretical contribution by operationalizing continuous authentication on zero trust and offers a practical system design of secure and scalable industrial connectivity.