A Trusted 3.0 Network Security Risk Assessment and Decision Support System Based on Discrete Rough Sets

Trusted computing, as a technology to improve the security of computer systems, has developed to the trusted 3.0 stage. This paper utilizes discrete rough set theory to research on trusted 3.0 network security. The trusted 3.0 network security decision support system constructed with B/S structure includes three modules: representation layer, business layer and data layer. In the rough set data analysis module, a network security risk assessment model is constructed based on discrete rough sets. The model preprocesses and discretizes the network security data, and constructs a knowledge base for risk assessment through attribute approximation and rule extraction. The risk assessment rules are extracted and utilized for risk assessment and decision support. The trusted 3.0 cybersecurity posture assessment under the methodology of this paper is very close to the expert’s expected results, with a maximum relative error of 2.54%, indicating that decisions can be made with reference to the assessment results of the model.