Survey on machine learning algorithms as cloud service for CIDPS

I. Avdagic, Kemal Hajdarevic
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引用次数: 5

Abstract

Today IT vendors and mail/web/internet providers put their cloud strategy in the first place. Challenges such as data security, privacy protection, data access, storage model, lack of standards and service interoperability were set up almost ten years ago. This paper presents a part of the research on the cloud security systems at the infrastructure layer and its sublayer — network layer. To analyze and protect cloud systems we need storage and machines with extra features. Due to these needs, we used new technologies from Microsoft to suggest framework of host and network based systems for cloud intrusion detection and prevention system (CIDPS). The purpose of this research is to recommend use of the architecture for the detection network anomalies and protection of large amounts of data and traffic generated by cloud systems.
机器学习算法作为CIDPS云服务的研究进展
今天,IT供应商和邮件/网络/互联网提供商把他们的云战略放在首位。数据安全、隐私保护、数据访问、存储模式、缺乏标准和服务互操作性等挑战几乎在十年前就存在了。本文对基础设施层及其子层——网络层的云安全系统进行了部分研究。为了分析和保护云系统,我们需要具有额外功能的存储和机器。基于这些需求,我们采用了微软的新技术,提出了基于主机和网络的云入侵检测与防御系统(CIDPS)框架。本研究的目的是推荐使用该架构来检测网络异常并保护云系统产生的大量数据和流量。
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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