将网络威胁情报映射到概率攻击图

A. Gylling, M. Ekstedt, Zeeshan Afzal, Per Eliasson
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引用次数: 4

摘要

随着网络威胁的持续增长和专业知识资源的有限,组织需要找到有效评估其弹性的方法,并在特定对手攻击发生之前采取主动措施。威胁建模是评估ICT系统弹性的一种极好的方法,形成攻击(防御)图(adg)来说明对手的攻击向量。网络威胁情报(CTI)是帮助了解当前网络威胁的信息,但与adg的集成很少。本文提出了一种解决这一问题的方法,即利用已知威胁参与者的CTI feed来丰富多重重用的adg。这使安全分析人员能够采取主动措施,加强他们的ICT系统,以应对任何被认为对他们构成威胁的威胁行为者所使用的当前方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping Cyber Threat Intelligence to Probabilistic Attack Graphs
As cyber threats continue to grow and expertise resources are limited, organisations need to find ways to evaluate their resilience efficiently and take proactive measures against an attack from a specific adversary before it occurs. Threat modelling is an excellent method of assessing the resilience of ICT systems, forming Attack (Defense) Graphs (ADGs) that illustrate an adversary’s attack vectors. Cyber Threat Intelligence (CTI) is information that helps understand the current cyber threats, but has little integration with ADGs. This paper contributes with an approach that resolves this problem by using CTI feeds of known threat actors to enrich ADGs under multiple reuse. This enables security analysts to take proactive measures and strengthen their ICT systems against current methods used by any threat actor that is believed to pose a threat to them.
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