Risk assessment of computer network information using a proposed approach: Fuzzy hierarchical reasoning model based on scientific inversion parallel programming

Abstract

Abstract Background Computer networks are involved in many fields such as business, education, marketing, government, and tourism in several forms. Technologies related to security protection and improvement of information integrity are used and developed for computer networks intruded on by unauthorized people and help save their confidentiality. Methods To improve the risk identification of computer networks, this manuscript combined a fuzzy hierarchical reasoning model with the scientific inversion parallel programming method to study the risk of computer networks. Moreover, this article defined and analyzed a d-order neighborhood message propagation algorithm. A d-order neighborhood parallel message propagation algorithm using the Gaussian graph model was proposed. Results The risk of the computer network was analyzed using the proposed method resulting in better protection effectiveness. Conclusion The simulations showed that the proposed algorithm could effectively detect risks and improve the security of the computer network.