Design and Development of inclusive finance Network Security System Model Based on Neural Network Algorithm

Design and Development of inclusive finance Network Security System Model Based on Neural Network Algorithm

연구 분야: Networking

학회: 2024 Asia-Pacific Conference on Software Engineering, Social Network Analysis and Intelligent Computing (SSAIC)

As an extension of traditional financial activities in the modern high-tech field, network finance realizes the safe and quick connection between financial institutions and customers through personal computers, communication terminals or other intelligent devices with the help of developed internet and communication technologies, thus facilitating customers to obtain economic and financial information in time, enjoy online financial services and carry out online financial transactions. During the evaluation of computer network security, some traditional assessment methods not only have the problems of low assessment accuracy and insufficient internal correlation research, but also have integrity problems. The interconnection of various factors adds complexity to the safety assessment process, rendering it a more challenging endeavor. In this article, a network security assessment algorithm of inclusive finance based on BP neural network is proposed, so as to create a network security assessment system with detection methods and risk assessment to ensure the security of financial network information. In the simulation results of network security assessment in inclusive finance, it can be seen that this model can get 94.7% recall and 96.8% accuracy rate, and its results are better than the compared model. The network security of financial industry has the characteristics of comprehensiveness, high technology and development, and the maintenance of network security should follow these characteristics.