Yang Li, Zou Kai, Gao Kai, Jiang Zhiyi
School of Public Administration, Xiangtan University, Xiangtan 411105, China.
The Library of Xiangtan University, Xiangtan 411105, China.
Math Biosci Eng. 2022 Dec 1;19(12):14232-14250. doi: 10.3934/mbe.2022662.
The rapid development of urban informatization is an important way for cities to achieve a higher pattern, but the accompanying information security problem become a major challenge restricting the efficiency of urban development. Therefore, effective identification and assessment of information security risks has become a key factor to improve the efficiency of urban development. In this paper, an information security risk assessment method based on fuzzy theory and neural network technology is proposed to help identify and solve the information security problem in the development of urban informatization. Combined with the theory of information ecology, this method establishes an improved fuzzy neural network model from four aspects by using fuzzy theory, neural network model and DEMATEL method, and then constructs the information security risk assessment system of smart city. According to this method, this paper analyzed 25 smart cities in China, and provided suggestions and guidance for information security control in the process of urban informatization construction.
城市信息化的快速发展是城市实现更高发展格局的重要途径，但随之而来的信息安全问题成为制约城市发展效率的重大挑战。因此，有效地识别和评估信息安全风险已成为提高城市发展效率的关键因素。本文提出一种基于模糊理论和神经网络技术的信息安全风险评估方法，以帮助识别和解决城市信息化发展中的信息安全问题。该方法结合信息生态理论，运用模糊理论、神经网络模型和决策试验与评价实验室（DEMATEL）方法，从四个方面建立了改进的模糊神经网络模型，进而构建智慧城市信息安全风险评估体系。依据该方法，本文对中国25个智慧城市进行了分析，并为城市信息化建设过程中的信息安全控制提供了建议和指导。
