Network security analysis for cloud computing environment

Linjiang Xie, Feilu Hang, W. Guo, Zhenhong Zhang, Hanruo Li
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引用次数: 2

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%.
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云计算环境下的网络安全分析
面向企业和消费者的信息技术服务可以通过使用云计算(CC)的互联网交付,因为它是敏捷的、具有成本效益的,并且经过了时间的考验。对于许多现实世界的应用程序,数据由第三方服务保存在云中,并根据需要通过Internet通过CC方法进行访问。与CC相关的风险涉及实时系统的数据安全和网络安全帐户。本文讨论了CC中的各种安全威胁,并通过设计一种基于机器学习的网络安全分析方案(NSA-ML)提出了解决方案。ML分类器预测网络漏洞,防止CC环境中的不安全通信。提出的NSA-ML提出了一种具有新颖加密方法的数据认证方案,以确保数据安全。实验结果表明,本文提出的NSA-ML方法的效率达到95.4%,优于现有的云安全方法。
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