面向云的组合MTD技术的综合安全评估

Hooman Alavizadeh, Jin B. Hong, Julian Jang, Dong Seong Kim
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引用次数: 26

摘要

移动目标防御(MTD)是一种主动安全解决方案,可以利用云计算来阻止网络攻击。已经提出了许多MTD技术,但是仍然缺乏系统的评估方法来评估所提出的MTD技术的有效性,特别是当多种MTD技术组合使用时。在本文中,我们的目标是通过提出一种MTD技术的建模和分析方法来解决上述问题。我们考虑了四个安全指标:系统风险、攻击成本、攻击回报和可用性,以便在部署MTD技术前后量化云的安全性。此外,我们提出了一种多样性MTD技术,用于在多个vm上部署具有各种变体的操作系统多样化,并结合Shuffle, Diversity和Redundancy MTD技术来提高云的安全性。我们在部署提议的技术之前和之后分析安全度量,以显示它们的有效性。我们还将基于网络中心性度量的重要性度量引入到安全分析阶段,以提高MTD评估的可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive Security Assessment of Combined MTD Techniques for the Cloud
Moving Target Defense (MTD) is a proactive security solution, which can be utilized by cloud computing in order to thwart cyber attacks. Many MTD techniques have been proposed, but there is still a lack of systematic evaluation methods for assessing the effectiveness of the proposed MTD techniques, especially when multiple MTD techniques are to be used in combinations. In this paper, we aim to address the aforementioned issue by proposing an approach for modeling and analysis of MTD techniques. We consider four security metrics: system risk, attack cost, return on attack, and availability to quantify the security of the cloud before and after deploying MTD techniques. Moreover, we propose a Diversity MTD technique to deploy OS diversification with various variants on multiple VMs and also combined Shuffle, Diversity, and Redundancy MTD techniques to improve the security of the cloud. We analyze the security metrics before and after deploying the proposed techniques to show the effectiveness of them. We also utilize importance measures based on network centrality measures into security analysis phase to improve the scalability of the MTD evaluation.
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