A Secure Convergence of Data Transmission and Intelligent Authentication Using a Sensing Approach for the Internet of Thing

Abstract

The IoT’s millions of sensor-equipped gadgets upload data to computers for management and use in smart grids, intelligent transportation networks, healthcare networks, and smart cities. Sensor data needs a safe server-sensor connection. Studying altered data could have catastrophic consequences. Internet-of-Things sensors must authenticate with the reader and base station before sending data. IoT sensors can securely and effectively communicate data. Correction evidence in the suggested technique reveals that the required data is created at the receiver using the normal Euclidean parameters of IoT sensors. The proposed approach is compatible with most assaults, making it a good security option. A framework for edge IoT devices can optimize latency, security, and other performance characteristics. Constraints Application Protocol (COAP) and The Stream Control Transmission Protocol (AESCQTTP) combine cooperative resource management, machine learning, context-aware computing, and flexible infrastructure to handle communication and computing difficulties. To reduce end-to-end latency by (7.13–7.35)%, raise security by 98.99%, and increase efficient pocket distribution to 98%. This study examined existing research issues and edge-computing technologies and proposed a novel strategy for optimizing edge-IoT system performance metrics. This arrangement could let future networks communicate securely.