{"title":"Network Information Security Monitoring Under Artificial Intelligence Environment","authors":"Longfei Fu, Yibin Liu, Yanjun Zhang, Ming Li","doi":"10.4018/ijisp.345038","DOIUrl":null,"url":null,"abstract":"At present, network attack means emerge in endlessly. The detection technology of network attack must be constantly updated and developed. Based on this, the two stages of network attack detection (feature selection and traffic classification) are discussed. The improved bat algorithm (O-BA) and the improved random forest algorithm (O-RF) are proposed for optimization. Moreover, the NIS system is designed based on the Agent concept. Finally, the simulation experiment is carried out on the real data platform. The results showed that the detection precision, accuracy, recall, and F1 score of O-BA are significantly higher than those of references [17], [18], [19], and [20], while the false positive rate is the opposite (P < 0.05). The detection precision, accuracy, recall, and F1 score of O-RF algorithm are significantly higher than those of Apriori, ID3, SVM, NSA, and O-RF algorithm, while the false positive rate is significantly lower than that of Apriori, ID3, SVM, NSA, and O-RF algorithm (P < 0.05).","PeriodicalId":44332,"journal":{"name":"International Journal of Information Security and Privacy","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Security and Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijisp.345038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
At present, network attack means emerge in endlessly. The detection technology of network attack must be constantly updated and developed. Based on this, the two stages of network attack detection (feature selection and traffic classification) are discussed. The improved bat algorithm (O-BA) and the improved random forest algorithm (O-RF) are proposed for optimization. Moreover, the NIS system is designed based on the Agent concept. Finally, the simulation experiment is carried out on the real data platform. The results showed that the detection precision, accuracy, recall, and F1 score of O-BA are significantly higher than those of references [17], [18], [19], and [20], while the false positive rate is the opposite (P < 0.05). The detection precision, accuracy, recall, and F1 score of O-RF algorithm are significantly higher than those of Apriori, ID3, SVM, NSA, and O-RF algorithm, while the false positive rate is significantly lower than that of Apriori, ID3, SVM, NSA, and O-RF algorithm (P < 0.05).
期刊介绍:
As information technology and the Internet become more and more ubiquitous and pervasive in our daily lives, there is an essential need for a more thorough understanding of information security and privacy issues and concerns. The International Journal of Information Security and Privacy (IJISP) creates and fosters a forum where research in the theory and practice of information security and privacy is advanced. IJISP publishes high quality papers dealing with a wide range of issues, ranging from technical, legal, regulatory, organizational, managerial, cultural, ethical and human aspects of information security and privacy, through a balanced mix of theoretical and empirical research articles, case studies, book reviews, tutorials, and editorials. This journal encourages submission of manuscripts that present research frameworks, methods, methodologies, theory development and validation, case studies, simulation results and analysis, technological architectures, infrastructure issues in design, and implementation and maintenance of secure and privacy preserving initiatives.