用于私有云的集中式HIDS框架

Zhijian Wang, Yanqin Zhu
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引用次数: 22

摘要

对于用户来说,云计算比传统的本地计算更方便、更高效,因为它为每个客户提供大规模的资源、软件和信息。然而,云计算系统很容易受到各种网络攻击的威胁。因此,一个入侵检测系统(IDS)对于云计算系统来说是非常必要的。传统的基于主机的云计算入侵检测系统存在着消耗大量系统资源的严重问题。在本文中,我们提出了一个集中式的基于主机的入侵检测框架,以减少资源的使用。使用logstash工具收集每个虚拟机的系统日志,并集中存储到elasticsearch集群中。之后,我们在检测中心分析所有这些日志,并将结果发送到每个虚拟机。我们已经在openstack平台上验证了我们的框架。结果表明,在降低CPU和内存使用方面具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A centralized HIDS framework for private cloud
Cloud computing is more convenient and efficient than traditional on-premise computing for users, as it provides large scale resources, software, and information to each customer. However, cloud computing systems can be easily threatened by various cyber attacks. Therefore, an Intrusion Detection System (IDS) is very necessary for cloud computing system. There is a serious problem which traditional host-based IDS for cloud computing consumes a large amount of system resources. In this paper, we propose a centralized host-based IDS framework to reduce the use of the resources. Using logstash tool to collect the system logs from each virtual machine, and storing them into elasticsearch cluster centrally. After that, we analyze all these logs in the detection center and send the results to each virtual machine. We have validated our framework in the openstack platform. The results show a good performance in reducing the CPU and memory usage.
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