# A Knowledge Graph-Based Consistency Detection Method for Network Security Policies
###### Abstract  
Network security policy is regarded as a guideline for the use and management of the network environment, which usually formulates various requirements in the form of natural language. It can help network managers conduct standardized network attack detection and situation awareness analysis in the overall time and space environment of network security. However, in most cases, due to configuration updates or policy conflicts, there are often differences between the real network environment and network security policies. In this case, the consistency detection of network security policies is necessary. The previous consistency detection methods of security policies have some problems. Firstly, the detection direction is single, only focusing on formal reasoning methods to achieve logical consistency detection and solve problems. Secondly, the detection policy field is not comprehensive, focusing only on a certain type of problem in a certain field. Thirdly, there are numerous forms of data structures used for consistency detection, and it is difficult to unify the structured processing and analysis of rule library carriers and target information carriers. With the development of intelligent graph and data mining technology, the above problems have the possibility of optimization. This article proposes a new consistency detection approach for network security policy, which uses an intelligent graph database as a visual information carrier, which can widely connect detection information and achieve comprehensive detection across knowledge domains, physical devices, and detection methods. At the same time, it can also help users grasp the security associations with the real network environment based on the graph algorithm of the knowledge graph and intelligent reasoning. Furthermore, these actual network situations and knowledge bases can help managers improve policies more tailored to local conditions. This article also introduces the consistency detection process of typical cases of network security policies, demonstrating the practical details and effectiveness of this method. s 2024 13 September 2024 16 September 202 network security has gradually shifted from a single security domain to a composite security domain. Therefore, consistency detection of security policies has been re-emphasized. At the same time, the development of knowledge graphs, data mining, and large language models has also brought new ideas for consistency detection of security policies. Knowledge graph technology can display complex knowledge domains through data mining, information processing, knowledge measurement, and graphical representation, thereby revealing the static and dynamic situations of the knowledge domain. It not only serves as a data carrier, but it can also minimize the time required to organize multiple different data sources into meaningful relationships, while possessing intelligent computing and reasoning capabilities [4; 5; 6]. Therefore, applying knowledge graphs to security policy consistency detection problems will have unique advantages. In this paper, we will innovatively use knowledge graphs to propose a new knowledge graph-based approach for consistency detection of network security policies by combining the existing experience of security policy consistency detection and knowledge graph technology. The main contributions of the new method are as follows:  
* Based on the task characteristics of policy consistency detection, we innovatively store the detection logic of policies in the knowledge graph and propose a four-layer knowledge graph structure for policy consistency detection tasks;
* A feasible formal approach in the task of policy consistency detection is given;
* The specific steps of using a knowledge graph for policy consistency detection are given, and at the same time, the characteristics of the knowledge graph that can carry out intelligent computation and reasoning are used to give the implementation methods of some extended functions related to policy consistency detection.