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Impact of Network Activity Levels on the Performance of Passive Network Service Dependency Discovery

机译:网络活动水平对被动网络服务依赖性发现性能的影响

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Network services often depend on other services distributed throughout a network to function correctly. If a service fails, is disrupted, or is degraded, it is likely to impair other services. The web of dependencies can be surprisingly complex--especially within a large enterprise network--and evolve over time. Acquiring, maintaining, and understanding dependency knowledge is critical for many network management and cyber defense activities, such as cyber mission mapping. While automation can improve situation awareness for network operators and cyber practitioners, poor detection performance reduces their confidence and can complicate their roles. In this paper, we study the effects of network activity levels on the detection performance of passive network-based service dependency discovery methods. The performance of all methods except for one were inconsistent with respect to network activity levels. Our proposed cross-correlation method was particularly robust to the influence of network activity. The proposed experimental treatment will further advance a more scientific evaluation of methods and provide a foundation to determine their operational boundaries.
机译:网络服务通常依赖于在整个网络中分布的其他服务正常运行。如果服务失败,则中断或劣化,可能会损害其他服务。依赖范围可以令人惊讶的复杂 - 尤其是在大型企业网络中 - 并随着时间的推移而发展。获取,维护和理解依赖知识对于许多网络管理和网络防御活动,例如网络使命映射。虽然自动化可以提高网络运营商和网络从业者的情况,但检测性能差可降低他们的信心,并可复杂化其角色。在本文中,我们研究了网络活动水平对基于被动网络的服务依赖性发现方法的检测性能的影响。除了一个外,所有方法的性能都与网络活动水平不一致。我们提出的互相关方法对网络活动的影响特别稳健。拟议的实验治疗将进一步推进对方法的更科学评估,并为确定其运营边界提供基础。

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