Directed graph security assessment based on authentication and trust estimation

In today's complex and dynamically changing network environment, ensuring system security is of utmost importance. This paper focuses on the research of directed graph security assessment based on authentication and trust estimation. By constructing a directed graph model, entities in the network are abstracted as nodes, and the relationships between entities are represented by directed edges. Advanced authentication technologies, such as multi-factor authentication and biometric identification, are used to strictly verify the identities of nodes, eliminating potential security risks caused by the access of illegal nodes to the network from the source. Meanwhile, with the help of trust estimation models based on historical interaction data and behavior pattern analysis, the trust level between nodes is quantified, taking into account factors such as trust transitivity and stability. By integrating the authentication results and trust estimation values, comprehensive security assessments of the directed graph are conducted using methods such as the Analytic Hierarchy Process and fuzzy comprehensive evaluation. The experimental results show that this assessment system can effectively identify security risk points in the network. Compared with traditional assessment methods, it has significant improvements in accuracy and timeliness. It provides strong support for network security protection decision-making and has broad application prospects in multiple fields such as social networks, the Internet of Things, and financial networks.