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Mitigating malicious packets attack via vulnerability-aware heterogeneous network devices assignment

机译:通过漏洞感知异构网络设备分配缓解恶意数据包攻击

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Due to high homogeneity of current network devices, a network is compromised if one node in the network is compromised by exploiting its vulnerability (e.g., malicious packets attack). Many existing works adopt heterogeneity philosophy to improve network survivability. For example, "diverse variants" are assigned to nodes in the network. However, these works assume that diverse variants do not have common vulnerabilities, which deem an invalid assumption in real networks. Therefore, existing diverse variants deployment schemes could not achieve optimal performance. This paper considers that some variants have common vulnerabilities, and proposes a novel solution called Vulnerability-aware Heterogeneous Network Devices Assignment (VHNDA). Firstly, we introduce a new metric named Expected Infected Ratio (EIR) to measure the impact of malicious packets' attacks spread on the network. Secondly, we use EIR to model the vulnerability-aware diverse variants deployment problem as an integer-programming optimization problem with NP-hard complexity. Considering NP-hardness, we then design a heuristic algorithm named Simulated Annealing Vulnerability-aware Diverse Variants Deployment (SA-VDVD) to address the problem. Finally, we present a low complexity algorithm named Graph Segmentation-based Simulated Annealing Vulnerability-aware Diverse Variants Deployment (GSSA-VDVD) for large-scale networks named graph segmentation-based simulated annealing. The experimental results demonstrate that the proposed algorithms restrain effectively the spread of malicious packets attack with a reasonable computation cost when compared with baseline algorithms.
机译:由于当前网络设备的高同质性,如果通过利用其漏洞(例如,恶意数据包攻击)泄露网络中的一个节点,则会泄压网络。许多现有的作品采用异质性哲学来提高网络生存能力。例如,“不同的变体”被分配给网络中的节点。但是,这些作品假设不同的变体没有常见的漏洞,这在真实网络中认为无效假设。因此,现有的不同变体部署方案无法实现最佳性能。本文认为某些变体具有常见漏洞,并提出了一种名为漏洞感知异构网络设备分配(VHNDA)的新型解决方案。首先,我们介绍了一个名为预期感染率(EIR)的新度量来衡量恶意数据包在网络上传播的影响。其次,我们使用EIR将漏洞感知的各种变体部署问题模拟为具有NP-Colly复杂性的整数编程优化问题。考虑到NP硬度,我们设计了一个名为模拟退火的启发式算法,该算法是模拟退火的漏洞感知的各种变体部署(SA-VDVD)以解决问题。最后,我们呈现了一种名为基于曲线分割的模拟退火的低复杂性算法,用于基于曲线分割的模拟退火的大规模网络的基于曲线基于模拟的模拟退火漏洞(GSSA-VDVD)。实验结果表明,与基线算法相比,所提出的算法有效地限制了恶意分组攻击的扩散与合理的计算成本。

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