Benchmarking Intrusion Detection Systems with Adaptive Provisioning of Virtualized Resources
Benchmarking Intrusion Detection Systems with Adaptive Provisioning of Virtualized Resources
复制标题
通过虚拟化资源的自适应配置对入侵检测系统进行基准测试
DOI：
10.1007/978-3-319-47474-8_22
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
Samuel Kounev
中科院分区：
文献类型：
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作者：
Aleksandar Milenkoski;K. R. Jayaram;Samuel Kounev
随着虚拟化的日益普及，在虚拟化环境中（例如，在虚拟机中作为虚拟化网络功能）部署入侵检测系统（IDS）已经成为新兴的实践。现代虚拟化环境的特点是按需向虚拟机提供虚拟化处理和存储器资源，动态地调整其强度以满足资源需求。这样的供应可能对部署在虚拟机中的IDS的许多属性（例如，对其攻击检测准确性）具有显著影响。然而，用于量化IDS攻击检测准确性的常规度量没有捕获这种影响，这可能导致IDS检测攻击的准确性的不准确评估。在本章中，我们将详细讨论按需提供虚拟化资源对IDS攻击检测准确性的影响。此外，我们讨论了有关使用传统的指标量化入侵检测系统的攻击检测精度的相关问题。最后，我们提出了一个初步的度量和测量方法，它允许准确评估IDS攻击检测的准确性，同时考虑到按需资源配置。
With the increasing popularity of virtualization, deploying intrusion detection systems (IDSes) in virtualized environments, for example, in virtual machines as virtualized network functions, has become an emerging practice. Modern virtualized environments feature on demand provisioning of virtualized processing and memory resources to virtual machines, dynamically adapting its intensity in order to meet resource demands. Such a provisioning may have a significant impact on many properties of an IDS deployed in a virtual machine, for example, on its attack detection accuracy. However, conventional metrics for quantifying IDS attack detection accuracy do not capture this impact, which may lead to inaccurate assessments of the IDS’s accuracy at detecting attacks. In this chapter, we discuss in detail on the impact of on demand provisioning of virtualized resources on IDS attack detection accuracy. Further, we discuss on relevant issues related to the use of conventional metrics for quantifying IDS attack detection accuracy. Finally, we present a preliminary metric and measurement methodologies, which allow for the accurate assessment of IDS attack detection accuracy taking on-demand resource provisioning into account.
DOI：
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发表时间：
2002
期刊：
International Symposium on Recent Advances in Intrusion Detection
影响因子：
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作者：
M. Hall;Kevin Wiley
通讯作者：
Kevin Wiley
分布式入侵检测环境中基于字符频率的自适应独占签名匹配方案
DOI：
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发表时间：
2012
期刊：
2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications
影响因子：
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作者：
Yuxin Meng;Wenjuan Li
通讯作者：
Wenjuan Li
通过在线模型估计虚拟化应用程序的运行时垂直扩展
DOI：
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发表时间：
2014
期刊：
2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems
影响因子：
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作者：
Simon Spinner;Samuel Kounev;Xiaoyun Zhu;Lei Lu;Mustafa Uysal;Anne M. Holler;Rean Griffith
通讯作者：
Rean Griffith