Tourism Investment Risk Analysis Model Based on Dynamic Network Security Strategy

Abstract

Traditional tourism investment risk analysis models mainly rely on static data and lack of sufficient consideration of dynamic change factors, resulting in the problem of time lag and insufficient accuracy of risk assessment results. To this end, this article constructs a tourism investment risk analysis model based on a dynamic network security strategy, aiming to achieve more real-time and precise risk assessment. By using the risk decomposition structure method, a comprehensive three-level tourism investment risk assessment index system is constructed. Dynamic Bayesian Network (DBN) is used to build a model that can parse network security data in real-time and assess the risk level of tourism investment, thereby significantly improving the accuracy and real-time performance of risk reasoning. A dynamic adjustment mechanism of network security strategy is constructed to enhance the security of tourism investment. The mechanism uses the CP-ABE (Ciphertext-Policy Attribute-based Encryption) algorithm to encrypt data, and combines role-based access control strategy to assign corresponding permissions to different roles in the tourism investment model. Experiments show that the risk analysis model based on DBN has an average risk assessment accuracy of 93.38%, a network security risk assessment detection response time of 2.62 seconds, and an investment return rate of 15.31%. The tourism investment risk analysis model studied in this article not only effectively makes up for the shortcomings of traditional models in timeliness and accuracy but also can significantly reduce investment risks and provide guarantees for the stable operation of tourism investment.