Evil Twins: Handling Repetitions in Attack–Defense Trees

Bossuat, Angèle; Kordy, Barbara

doi:10.1007/978-3-319-74860-3_2

Cited by 17 publications

(16 citation statements)

References 13 publications

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“…In particular, following [5], we call a basic action that serves as a label for at least two nodes a clone or a cloned basic action, and interpret them as the same instance of a goal. Nodes representing distinct instances of the same goal or distinct goals are assumed in this work to have different labels.…”

Section: Attack-defense Treesmentioning

confidence: 99%

“…Such approach might not always be desirable, especially when we do not only want to know whether attacks are possible, but actually how they can be achieved. To accommodate this point of view, the set semantics has recently been introduced in [5]. We briefly recall its construction below.…”

Section: Definition 1 the Propositional Semantics For Attack-defensementioning

confidence: 99%

“…In some works the problem is avoided (or overlooked) by interpretation of repeated labels as distinct instances of the same goal, thus, de facto as distinct goals (e.g., [8,13,18,22]), or by distinguishing between the repetitions occurring in specific subtrees of a tree, as in [3]. Recently, Bossuat and Kordy have established a classification of repeated labels in attackdefense trees, depending on whether the corresponding nodes represent exactly the same instance or different instances of a goal [5]. They point out that, if the meaning of repeated labels is not properly specified, then the fast, bottom-up method for identifying attacks that optimize an attribute (e.g., minimal cost, probability of success, etc.…”

Section: Introductionmentioning

confidence: 99%

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On Quantitative Analysis of Attack–Defense Trees with Repeated Labels

Kordy

Wideł

2018

Lecture Notes in Computer Science

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Abstract. Ensuring security of complex systems is a difficult task that requires utilization of numerous tools originating from various domains. Among those tools we find attack-defense trees, a simple yet practical model for analysis of scenarios involving two competing parties. Enhancing the well-established model of attack trees, attack-defense trees are trees with labeled nodes, offering an intuitive representation of possible ways in which an attacker can harm a system, and means of countering the attacks that are available to the defender. The growing palette of methods for quantitative analysis of attack-defense trees provides security experts with tools for determining the most threatening attacks and the best ways of securing the system against those attacks. Unfortunately, many of those methods might fail or provide the user with distorted results if the underlying attack-defense tree contains multiple nodes bearing the same label. We address this issue by studying conditions ensuring that the standard bottom-up evaluation method for quantifying attack-defense trees yields meaningful results in the presence of repeated labels. For the case when those conditions are not satisfied, we devise an alternative approach for quantification of attacks.

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Section: Attack-defense Treesmentioning

confidence: 99%

Section: Definition 1 the Propositional Semantics For Attack-defensementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On Quantitative Analysis of Attack–Defense Trees with Repeated Labels

Kordy

Wideł

2018

Lecture Notes in Computer Science

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“…Static DAGs: It is well-known that static attack trees with DAG structure cannot be analysed via a bottom-up procedure [21,23]. Several algorithms have been devised to tackle with such ATs, mostly geared to specific metrics [5,17,12,7,18].…”

Section: Open Problemmentioning

confidence: 99%

Efficient Algorithms for Quantitative Attack Tree Analysis

Budde¹,

Stoelinga²

2021

Preprint

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Numerous analysis methods for quantitative attack tree analysis have been proposed. These algorithms compute relevant security metrics, i.e. performance indicators that quantify how good the security of a system is, such as the most likely attack, the cheapest, or the most damaging one. This paper classifies attack trees in two dimensions: proper trees vs. directed acyclic graphs (i.e. with shared subtrees); and static vs. dynamic gates. For each class, we propose novel algorithms that work over a generic attribute domain, encompassing a large number of concrete security metrics defined on the attack tree semantics. We also analyse the computational complexity of our methods.

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“…In particular, if O = ∅, then the proponent executing all of the actions from P achieves the root goal, regardless of the behavior of the opponent. The set semantics was first introduced in [7] and was then used in [2], where quantitative analysis of ADTrees with repeated labels has been studied. We recall the construction of the set semantics in Definition 1.…”

Section: Example 1 In the Scenario Represented By The Adtree Frommentioning

confidence: 99%

Efficient Attack-Defense Tree Analysis using Pareto Attribute Domains

Fila

Wideł

2019

2019 IEEE 32nd Computer Security Foundations Symposium (CSF)

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The cheapest attacks are often time-consuming, and those requiring high level of technical skills might occur rarely but result in disastrous consequences. Therefore, analysis focusing on a single parameter at a time, e.g., only cost or time, is insufficient for the successful selection of the appropriate measures increasing system's security. In practice, security engineers are thus confronted with the problem of multi-parameter analysis. The objective of this work is to address this problem and propose a sound, general framework for multi-parameter analysis of security. In order to ensure the usability of our solution for real-life applications, our proposal relies on the attackdefense tree model that security experts from industry are already familiar with. We present mathematical foundations of our framework and characterize the class of parameters it is suitable for. We identify conditions under which the proposed method applies to attack-defense trees where several nodes represent the same action. We discuss the complexity of our approach and implement the underlying algorithms in a proof of concept tool. We analyze its performance on a number of trees of varying complexity, and validate our proposal on a case study borrowed from industry.

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Evil Twins: Handling Repetitions in Attack–Defense Trees

Cited by 17 publications

References 13 publications

On Quantitative Analysis of Attack–Defense Trees with Repeated Labels

On Quantitative Analysis of Attack–Defense Trees with Repeated Labels

Efficient Algorithms for Quantitative Attack Tree Analysis

Efficient Attack-Defense Tree Analysis using Pareto Attribute Domains

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