Machine Learning based Security for Cloud Computing: A Survey

Q1 Engineering
M. Saran, R. Yadav, U. Tripathi
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引用次数: 3

Abstract

Cloud computing is a computing paradigm that provides on-demand, scalable as well as measured services to the end uses. In today’s era almost each and every business has huge dependency on this computing technology in terms of cost-saving, infrastructure, development platform, data processing, data analytics etc. The services provided by the cloud service providers (CSP) can be consumed by the end users anytime, anywhere by the web application over the internet. The security of the cloud infrastructure is of utmost importance and several research work involving various technologies are utilized so as to provide better and more accurate defence mechanism against cloud attacks. Machine learning is a technology that has proved to produce better results in securing the cloud environment in the recent times. Machine learning algorithms are trained on the various authentic datasets to build models that can automate the process of detecting the cloud attacks with higher accuracy in comparison with any other technology. This paper reviews some of the latest research papers that have employed machine learning as a security mechanism against cloud attacks.
基于机器学习的云计算安全:调查
云计算是一种计算范式,它为最终用户提供按需、可扩展和可衡量的服务。在当今时代,几乎每个企业在节约成本、基础设施、开发平台、数据处理、数据分析等方面都非常依赖这种计算技术。云服务提供商(CSP)提供的服务可以通过web应用程序在互联网上随时随地被最终用户使用。云基础设施的安全性至关重要,为了提供更好、更准确的云攻击防御机制,我们开展了多项涉及多种技术的研究工作。近年来,机器学习技术已被证明在保护云环境方面能产生更好的结果。机器学习算法在各种真实数据集上进行训练,以构建模型,与任何其他技术相比,这些模型可以以更高的精度自动检测云攻击的过程。本文回顾了一些最新的研究论文,这些论文采用机器学习作为对抗云攻击的安全机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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