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Cyber Security Analysis using Attack Countermeasure Trees

机译:网络安全分析采用攻击对策树木

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Attack tree (AT) is one of the widely used combinatorial models in cyber security analysis. The basic formalism of AT does not take into account defense mechanisms. Defense trees (DT) have been developed to investigate the effect of defense mechanisms using measures such as attacker's cost and security cost, return on investment (ROI) and return on attack (ROA). DT, however, places defense mechanisms only at the leaf node level while the corresponding ROI/ROA analysis does not incorporate the probability of attack. In attack response tree (ART), attacker-defender game was used to fin optimal policy from the countermeasures' pool and it suffers from the problem of state-space explosion, since solution in ART is resolved by means of a partially observable stochastic game model. In this paper, we present a novel attack tree named attack countermeasure trees' (ACT) in which (i) defense mechanisms can be applied at any node of the tree, not just at leaf node level, (ii) qualitative analysis (using mincuts, structural and Birnbaum importance measure) and probabilistic analysis (using attacker and security cost, system risk, impact of an attack, ROI and ROA) can be performed (iii) optimal countermeasure set can be selected from the pool of defense mechanisms without constructing a state-space model. We use single and multi-objective optimization to fin suitable countermeasures under different constraints. We illustrate the features of ACT using a practical case study (SCADA attack).
机译:攻击树(AT)是在网络安全分析中广泛使用的组合模型之一。 AT基本形式主义不考虑防御机制。国防部树(DT)已发展到调查的防御机制使用,如攻击者的成本和安全成本,投资回报(ROI)和攻击(ROA)回报收益措施的效果。 DT,然而,则以防御机制只在叶节点级别,而相应的投资回报率/资产回报率分析不包含攻击的可能性。在攻击响应树(ART),攻击者后卫游戏是用来鳍最优政策与对策池并从状态空间爆炸问题的困扰,因为在技术的解决方案是由部分可观察随机博弈模型来解决。在本文中,我们提出了一个名为攻击对策树(动作),其中(i)防御机制,可以在树的任何节点应用,不只是在叶节点级别的一种新型攻击树,(二)定性分析(使用mincuts ,结构和伯恩鲍姆重要指标)和概率分析(使用攻击者和安全成本,系统风险,攻击,投资回报率和ROA)的影响,可以进行(III)最佳对策集可以从防御机制池中选择,而没有构建状态空间模型。我们使用单和多目标优化,在不同的约束鳍适当的对策。我们说明使用一个实际案例研究(SCADA攻击)的行为特征。

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