Linjiang Xie, Feilu Hang, W. Guo, Zhenhong Zhang, Hanruo Li
{"title":"云计算环境下的网络安全分析","authors":"Linjiang Xie, Feilu Hang, W. Guo, Zhenhong Zhang, Hanruo Li","doi":"10.1142/s1793962322500544","DOIUrl":null,"url":null,"abstract":"Information technology services for businesses and consumers can be delivered via the Internet using cloud computing (CC) because it is agile, cost-effective, and time-tested. For many real-world applications, the data are kept in the cloud by a third-party service and accessible through the Internet as needed through CC approaches. Risks associated with CC involve the data security and network security account for real-time systems. This paper discusses different security threats in CC and suggests a solution by designing a network security analysis scheme with machine learning (NSA-ML). The ML classifier predicts the network vulnerabilities and prevents insecure communication in a CC environment. The proposed NSA-ML presents a data authentication scheme with a novel encryption methodology to ensure data security. The experimental results show that the proposed NSA-ML outperforms the existing cloud security approaches by gaining an efficiency of 95.4%.","PeriodicalId":13657,"journal":{"name":"Int. J. Model. Simul. Sci. Comput.","volume":"64 1","pages":"2250054:1-2250054:20"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Network security analysis for cloud computing environment\",\"authors\":\"Linjiang Xie, Feilu Hang, W. Guo, Zhenhong Zhang, Hanruo Li\",\"doi\":\"10.1142/s1793962322500544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Information technology services for businesses and consumers can be delivered via the Internet using cloud computing (CC) because it is agile, cost-effective, and time-tested. For many real-world applications, the data are kept in the cloud by a third-party service and accessible through the Internet as needed through CC approaches. Risks associated with CC involve the data security and network security account for real-time systems. This paper discusses different security threats in CC and suggests a solution by designing a network security analysis scheme with machine learning (NSA-ML). The ML classifier predicts the network vulnerabilities and prevents insecure communication in a CC environment. The proposed NSA-ML presents a data authentication scheme with a novel encryption methodology to ensure data security. The experimental results show that the proposed NSA-ML outperforms the existing cloud security approaches by gaining an efficiency of 95.4%.\",\"PeriodicalId\":13657,\"journal\":{\"name\":\"Int. J. Model. Simul. Sci. Comput.\",\"volume\":\"64 1\",\"pages\":\"2250054:1-2250054:20\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Model. Simul. Sci. Comput.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s1793962322500544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Model. Simul. Sci. Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s1793962322500544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Network security analysis for cloud computing environment
Information technology services for businesses and consumers can be delivered via the Internet using cloud computing (CC) because it is agile, cost-effective, and time-tested. For many real-world applications, the data are kept in the cloud by a third-party service and accessible through the Internet as needed through CC approaches. Risks associated with CC involve the data security and network security account for real-time systems. This paper discusses different security threats in CC and suggests a solution by designing a network security analysis scheme with machine learning (NSA-ML). The ML classifier predicts the network vulnerabilities and prevents insecure communication in a CC environment. The proposed NSA-ML presents a data authentication scheme with a novel encryption methodology to ensure data security. The experimental results show that the proposed NSA-ML outperforms the existing cloud security approaches by gaining an efficiency of 95.4%.