An intelligent method of data integrity detection based on multi-modality fusion convolutional neural network in industrial control network

Abstract

Industrial control network can be connected with deep learning to trigger the intelligent contract by the output of deep learning, or take the implementation result of intelligent contract as the input of deep learning. In order to solve the problem of missing values when collecting a large number of high-dimensional data in industrial process control system, this paper proposes a intelligent method of data integrity detection based on multi-modality fusion CNN (Convolutional Neural Network) in industrial control network, which provides reliable support for the storage of industrial control detection data. The proposed method takes industrial control system as the research object, aiming at the specific problems of data integrity detection, combines with convolution neural network. The experimental results show that the proposed method can effectively ensure the safety of data in the industrial control network data transmission, and can extract effective information from a large number of high-dimensional data.