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At present, most network security analysis theory assumes that the players are completely rational. However, this is not consistent with the actual situation. In this paper, based on the effectiveness constraints on both sides with network attack and defense, with the help of stochastic Petri net and evolutionary game theory, the Petri net model of network attack and defense stochastic evolutionary game is reconstructed, the specific definition of the model is given, and the modeling method is given through the network connection relationship and attack and defense strategy set. Using this model, a quantitative analysis of network attack events is carried out to solve a series of indicators related to system security, namely, attack success rate, average attack time, and average system repair time. Finally, the proposed model and analysis method are applied to a classic network attack and defense process for experimental analysis, and the results verify the rationality and accuracy of the model and analysis method.

With the development of society and information technology, people’s dependence on the Internet has gradually increased, including online shopping, downloading files, reading books, and online banking. However, how to ensure the safety and legitimacy of these network user behaviors has become the focus of attention. As we all know, cybersecurity and system resilience originate from symmetry. Due to the diversity and unpredictability of cyber-attacks, absolute cybersecurity is difficult to achieve; system resilience indicates that protecting system security should shift from resisting attacks to ensuring system continuity. The trust evaluation of network users is a research hotspot in improving network system security. Aiming at the defects of incomplete evaluation processes and inaccurate evaluation results in current online user behavior trust evaluation methods, this paper combines the basic principles of online user trust evaluation and proposes a trust evaluation model that combines fuzzy Petri nets with user behavior analysis. First, for “unfamiliar” users, we used fuzzy Petri nets to calculate the user’s recommended trust value as the system’s indirect trust value; next, we used the user’s behavior record as evidence to conduct direct trust evaluation on the user to obtain the system’s direct trust in the user’s value; finally, the two calculation results were combined to obtain the user’s comprehensive trust value. In terms of experimental verification, the experimental data came from a self-developed e-book management system. Through theoretical analysis and simulation results, it was shown that the model met the optimization conditions of subjective and objective relative balance, the evaluation process was more complete, and the trust evaluation values of network users could be obtained more accurately. This evaluation method provides solid theory and research ideas for user credibility judgment of key network basic application platforms such as online shopping malls, online transactions, and online banking.