Guided Design of Attack Trees: A System-Based Approach

Audinot, Maxime; Pinchinat, Sophie; Kordy, Barbara

doi:10.1109/csf.2018.00012

Cited by 16 publications

(15 citation statements)

References 14 publications

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“…The resulting attack trees tend to be diverse, which poses a problem from a practical viewpoint. Although several studies [5,9,10] have addressed to this issue, the frameworks they proposed are rather indirect. Therefore, methodologies need to be developed for considering the consistency of attack trees simply.…”

Section: Problem and Resultsmentioning

confidence: 99%

“…To the best of our knowledge, most related studies have explicitly discussed neither guidance for attack decompositions nor the validity of decompositions in detail. Although the research [5,9,10] discussed this issue, their frameworks dealt with attacks only indirectly.…”

Section: Overview Of Attack Treesmentioning

confidence: 99%

“…Typ(FD(C)) is subject to relations 5 of distributive lattices and semantical relations among primitive types, that is the resulting lattice is not always a free-generated 6 . • For a primitive type α µ , {a λ } λ∈Λ FD(C) α µ ⇐⇒ µ ∈ Λ and a µ C α.…”

Section: The Classificationmentioning

confidence: 99%

“…Attack trees are a major tool in analyzing the security of a system [2][3][4][5], as they represent the decomposition of threats in the form of AND/OR-trees, alongside fault trees that represent the structures of faults in a system in the safety domain. As shown in the following example and Section 2, attack trees match formal approaches in that they enable us to understand a threat's logical structures and estimate its qualitative/quantitative properties.…”

mentioning

confidence: 99%

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On Validating Attack Trees with Attack Effects: An Approach from Barwise-Seligman's Channel Theory

Nishihara¹,

Kawanishi²,

Souma³

et al. 2022

Preprint

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In security analysis, attack trees are a major tool for showing the structural decomposition of attacks and for supporting the evaluation of the quantitative properties (called attributes) of the attacks. However, the validities of decompositions are not established by attack trees themselves, and fallacious decisions about security may be made when the attack trees are inaccurate. This paper enriches attack trees with effects of attacks, with a formal system focusing on refinement scenarios. Relationships among effects indicate relationships among attacks and it allows for a systematic evaluation of attack decompositions. To describe effects this paper applies Barwise-Seligman's channel theory. Infomorphisms, in particular, play a significant role to connect effects with distinct granularities. As a result, the consistency of a decomposition is formally defined and a condition for it is stated. This framework is applied to a case study of a vehicular network system. As an application of the idea of consistency, possible degrees of mitigation for attacks in attack trees are discussed.

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Section: Problem and Resultsmentioning

confidence: 99%

Section: Overview Of Attack Treesmentioning

confidence: 99%

Section: The Classificationmentioning

confidence: 99%

mentioning

confidence: 99%

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On Validating Attack Trees with Attack Effects: An Approach from Barwise-Seligman's Channel Theory

Nishihara¹,

Kawanishi²,

Souma³

et al. 2022

Preprint

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“…Attack Trees [21] [22] are a prime example of attack graphs. Their success lies in the ability to provide information on how an attacker can achieve a goal in an intuitive way through simple logical operations of conjunction and disjunction between sub-activity.…”

Section: Attack Treementioning

confidence: 99%

Bio-inspired security analysis for IoT scenarios

Conti¹,

Ziggiotto²,

Migliardi³

et al. 2020

IJES

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Computer security has recently become more and more important as the world economy dependency from data has kept growing. The complexity of the systems that need to be kept secure calls for new models capable of abstracting the interdependencies among heterogeneous components that cooperate at providing the desired service. A promising approach is attack graph analysis, however, the manual analysis of attack graphs is tedious and error prone. In this paper we propose to apply the metabolic network model to attack graphs analysis, using three interacting bio-inspired algorithms: topological analysis, flux balance analysis, and extreme pathway analysis. A developed framework for graph building and simulations as well as an introductory to some IoT scenarios as use cases are also outlined.

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