User Behavior Monitoring Mechanism of Online Shopping Processes based on Hierarchical Colored Petri Net

Online shopping has developed very rapidly with the rise of economy, but due to its open network environment, many security issues have also appeared. Among them, behavior risk has become a new security challenge in the online shopping process. Thus, this paper proposes a monitoring mechanism for the behavior risk of online shopping users. Once there is risky information in the user’s session, it can be monitored and processed in time. In this paper, the modeling method based on Hierarchical Colored Petri Net (HCPN) is used to depict the monitoring mechanism, and the CPNTools is used to generate the state space diagram to validate the correctness of the model. This monitoring mechanism supplements the analysis theory of user behavior risk during online shopping processes. The proposed method can be used to protect consumers’ legitimate interests in real-time.