Network Security and Privacy Security in the IoT Environment

Abstract

The Internet of things is the second major revolution based on the Internet. It realizes the purpose of connecting things and promotes the development of economy and society. In order to ensure the security of the Internet of things environment, network security and privacy security become the primary problem to be solved. Based on the above background, the purpose of this paper is to study the analysis of network security and privacy security in the Internet of things environment. In order to describe the implicit information among the situation elements in the index system intuitively, this paper proposes a network security and privacy security situation assessment method based on PSO-MCELman, and a network security and privacy security situation prediction method based on PSO-MCELman according to the timing characteristics of situation prediction data. When each method completes the situation prediction training, the PSO-MCELman neural network proposed in this paper The least number of network iterations is 23, which is 22, 14 and 5 times less than traditional Elman, GA-Elman and PSO-Elman neural networks. Through the prediction of network security and privacy security situation, users can be more aware of the importance of Internet of things security and privacy security, and hope to provide some help for the solution of Internet of things security and user privacy security.