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Function and activity classification in network traffic data: existing methods, their weaknesses, and a path forward

机译:网络流量数据中的功能和活动分类:现有方法,它们的弱点和前进的道路

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The cyber spaces are increasingly becoming the battlefields between friendly and adversary forces, with normal users caught in the middle. Accordingly, planners of enterprise defensive policies and offensive cyber missions alike have an essential goal to minimize the impact of their own actions and adversaries' attacks on normal operations of the commercial and government networks. To do this, the cyber analysis need accurate "cyber battle maps", where the functions, roles, and activities of individual and groups of devices and users are accurately identified.Most of the research in cyber exploitation has focused on the identification of attacks, attackers, and their devices. Many tools exist for device profiling, malware identification, user attribution, and attack analysis. However, most of the tools are intrusive, sensitive to data obfuscation, or provide anomaly flagging and not able to correctly classify the semantics and causes of network activities, hi this paper, we review existing solutions that can identify functional and social roles of entities in cyberspace, discuss their weaknesses, and propose an approach for developing functional and social layers of cyber battle maps.
机译:网络空间正日益成为友好力量和敌对力量之间的战场,普通用户陷入其中。因此,企业防御策略和攻击性网络任务的计划者都具有一个基本目标,即最大程度地减少自己的行为和对手的攻击对商业和政府网络正常运行的影响。为此,网络分析需要准确的“网络战图”,在其中可以准确识别个人,设备组和用户的功能,角色和活动。网络开发中的大部分研究都集中在攻击的识别,攻击者及其设备。存在许多用于设备性能分析,恶意软件识别,用户归因和攻击分析的工具。但是,大多数工具都是侵入性的,对数据混淆敏感,或者提供异常标记,并且无法正确分类网络活动的语义和原因。在本文中,我们回顾了可以识别实体功能和社会角色的现有解决方案。网络空间,讨论他们的弱点,并提出一种开发网络战图功能和社交层的方法。

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