Research on Information Security Evaluation Based on Artificial Neural Network
Title | Research on Information Security Evaluation Based on Artificial Neural Network |
Publication Type | Conference Paper |
Year of Publication | 2020 |
Authors | Zhang, Yunxiang, Rao, Zhuyi |
Conference Name | 2020 3rd International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) |
Keywords | artificial intelligence security, artificial neural network, Artificial neural networks, cyber physical systems, evaluation, Information encryption, Information security, Metrics, policy-based governance, pubcrawl, Resiliency |
Abstract | In order to improve the information security ability of the network information platform, the information security evaluation method is proposed based on artificial neural network. Based on the comprehensive analysis of the security events in the construction of the network information platform, the risk assessment model of the network information platform is constructed based on the artificial neural network theory. The weight calculation algorithm of artificial neural network and the minimum artificial neural network pruning algorithm are also given, which can realize the quantitative evaluation of network information security. The fuzzy neural network weighted control method is used to control the information security, and the non-recursive traversal method is adopted to realize the adaptive training of information security assessment process. The adaptive learning of the artificial neural network is carried out according to the conditions, and the ability of information encryption and transmission is improved. The information security assessment is realized. The simulation results show that the method is accurate and ensures the information security. |
DOI | 10.1109/AEMCSE50948.2020.00098 |
Citation Key | zhang_research_2020 |