A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network

Abstract

One of the most popular technological frameworks of the year is without a certain Internet of Things (IoT). It permeates numerous industries and has a profound impact on people's lives in all spheres. The “Internet of everything” age is by the IoT technology's rapid development, but it also alters the function of terminal equipment at the network's edge. The name “Internet of Things” has evolved as a result enabling things to be intelligent and competent in talking with verified devices (IoT). Between smart devices, social IoT (IoT) devices interact and adopt social networking concepts. It takes a secure connection between the smart gadgets to enable sociability. To determine whether the suggested strategy is practical it is applied to a convolutional neural network (CNN)-based language similarity analysis model in the context. The model created using the encounter training method is more accurate than the original CNN.