{"title":"基于GRA-BPNN的智慧城市网络信息安全评估模型构建","authors":"Xiang Li","doi":"10.13052/jcsm2245-1439.1162","DOIUrl":null,"url":null,"abstract":"In this study, we propose an optimized network information security evaluation GRA-BPNN model based on gray correlation analysis method combined with BP neural network model, and make corresponding optimization for network information security evaluation index. Simulation experiments are conducted to analyze the experimental model, and the simulation results show that the test sample values reach the best training performance at the 7th iteration after 13 iterations, and the R-values in the regression of training results all reach above 0.99, and the data are well-fitted. When the number of training iterations reaches 13, the training gradient is 0.00067928, the value of Mu is 0.001, and the validity test value is 6. The GRA-BPNN model scores 0.028 higher than the GRA method, which is in line with the expected error, and the higher score also proves that the GRA-BPNN model is more comprehensive and specific in its scoring consideration.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"83 1","pages":"755-776"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Construction of a Smart City Network Information Security Evaluation Model Based on GRA-BPNN\",\"authors\":\"Xiang Li\",\"doi\":\"10.13052/jcsm2245-1439.1162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we propose an optimized network information security evaluation GRA-BPNN model based on gray correlation analysis method combined with BP neural network model, and make corresponding optimization for network information security evaluation index. Simulation experiments are conducted to analyze the experimental model, and the simulation results show that the test sample values reach the best training performance at the 7th iteration after 13 iterations, and the R-values in the regression of training results all reach above 0.99, and the data are well-fitted. When the number of training iterations reaches 13, the training gradient is 0.00067928, the value of Mu is 0.001, and the validity test value is 6. The GRA-BPNN model scores 0.028 higher than the GRA method, which is in line with the expected error, and the higher score also proves that the GRA-BPNN model is more comprehensive and specific in its scoring consideration.\",\"PeriodicalId\":37820,\"journal\":{\"name\":\"Journal of Cyber Security and Mobility\",\"volume\":\"83 1\",\"pages\":\"755-776\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cyber Security and Mobility\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13052/jcsm2245-1439.1162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cyber Security and Mobility","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/jcsm2245-1439.1162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Construction of a Smart City Network Information Security Evaluation Model Based on GRA-BPNN
In this study, we propose an optimized network information security evaluation GRA-BPNN model based on gray correlation analysis method combined with BP neural network model, and make corresponding optimization for network information security evaluation index. Simulation experiments are conducted to analyze the experimental model, and the simulation results show that the test sample values reach the best training performance at the 7th iteration after 13 iterations, and the R-values in the regression of training results all reach above 0.99, and the data are well-fitted. When the number of training iterations reaches 13, the training gradient is 0.00067928, the value of Mu is 0.001, and the validity test value is 6. The GRA-BPNN model scores 0.028 higher than the GRA method, which is in line with the expected error, and the higher score also proves that the GRA-BPNN model is more comprehensive and specific in its scoring consideration.
期刊介绍:
Journal of Cyber Security and Mobility is an international, open-access, peer reviewed journal publishing original research, review/survey, and tutorial papers on all cyber security fields including information, computer & network security, cryptography, digital forensics etc. but also interdisciplinary articles that cover privacy, ethical, legal, economical aspects of cyber security or emerging solutions drawn from other branches of science, for example, nature-inspired. The journal aims at becoming an international source of innovation and an essential reading for IT security professionals around the world by providing an in-depth and holistic view on all security spectrum and solutions ranging from practical to theoretical. Its goal is to bring together researchers and practitioners dealing with the diverse fields of cybersecurity and to cover topics that are equally valuable for professionals as well as for those new in the field from all sectors industry, commerce and academia. This journal covers diverse security issues in cyber space and solutions thereof. As cyber space has moved towards the wireless/mobile world, issues in wireless/mobile communications and those involving mobility aspects will also be published.