Calculating Adversarial Risk from Attack Trees: Control Strength and Probabilistic Attackers

Wolter Pieters, Mohsen Davarynejad

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)

Abstract

Attack trees are a well-known formalism for quantitative analysis of cyber attacks consisting of multiple steps and alternative paths. It is possible to derive properties of the overall attacks from properties of individual steps, such as cost for the attacker and probability of success. However, in existing formalisms, such properties are considered independent. For example, investing more in an attack step would not increase the probability of success. As this seems counterintuitive, we introduce a framework for reasoning about attack trees based on the notion of control strength, annotating nodes with a function from attacker investment to probability of success. Calculation rules on such trees are defined to enable analysis of optimal attacker investment. Our second result consists of the translation of optimal attacker investment into the associated adversarial risk, yielding what we call adversarial risk trees. The third result is the introduction of probabilistic attacker strate- gies, based on the fitness (utility) of available scenarios. Together these contributions improve the possibilities for using attack trees in adversarial risk analysis.
Original languageEnglish
Title of host publicationData Privacy Management, Autonomous Spontaneous Security, and Security Assurance
Subtitle of host publication9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers
EditorsJoaquin Garcia-Alfaro, Jordi Herrera-Joancomartí, Emil Lupu, Joachim Posegga
Place of PublicationBerlin
PublisherSpringer
Pages201-215
Number of pages15
ISBN (Electronic)978-3-319-17016-9
ISBN (Print)978-3-319-17015-2
DOIs
Publication statusPublished - 28 Mar 2015
Event3rd International Workshop on Quantitative Aspects in Security Assurance, QASA 2014 - Wraclaw, Poland
Duration: 10 Sep 201411 Sep 2014
Conference number: 3

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume8872
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Workshop

Workshop3rd International Workshop on Quantitative Aspects in Security Assurance, QASA 2014
Abbreviated titleQASA
CountryPoland
CityWraclaw
Period10/09/1411/09/14

Fingerprint

Trees (mathematics)
Risk analysis
Chemical analysis
Costs

Keywords

  • EC Grant Agreement nr.: FP7/318003
  • SCS-cybersecurity
  • EC Grant Agreement nr.: FP7/2007-2013
  • Control strength
  • Security metrics
  • Adversarial risk analysis
  • Attack trees
  • Attacker models
  • Fitness functions
  • Simulation

Cite this

Pieters, W., & Davarynejad, M. (2015). Calculating Adversarial Risk from Attack Trees: Control Strength and Probabilistic Attackers. In J. Garcia-Alfaro, J. Herrera-Joancomartí, E. Lupu, & J. Posegga (Eds.), Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance: 9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers (pp. 201-215). (Lecture Notes in Computer Science; Vol. 8872). Berlin: Springer. https://doi.org/10.1007/978-3-319-17016-9_13
Pieters, Wolter ; Davarynejad, Mohsen. / Calculating Adversarial Risk from Attack Trees : Control Strength and Probabilistic Attackers. Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance: 9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers. editor / Joaquin Garcia-Alfaro ; Jordi Herrera-Joancomartí ; Emil Lupu ; Joachim Posegga. Berlin : Springer, 2015. pp. 201-215 (Lecture Notes in Computer Science).
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Pieters, W & Davarynejad, M 2015, Calculating Adversarial Risk from Attack Trees: Control Strength and Probabilistic Attackers. in J Garcia-Alfaro, J Herrera-Joancomartí, E Lupu & J Posegga (eds), Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance: 9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers. Lecture Notes in Computer Science, vol. 8872, Springer, Berlin, pp. 201-215, 3rd International Workshop on Quantitative Aspects in Security Assurance, QASA 2014, Wraclaw, Poland, 10/09/14. https://doi.org/10.1007/978-3-319-17016-9_13

Calculating Adversarial Risk from Attack Trees : Control Strength and Probabilistic Attackers. / Pieters, Wolter; Davarynejad, Mohsen.

Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance: 9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers. ed. / Joaquin Garcia-Alfaro; Jordi Herrera-Joancomartí; Emil Lupu; Joachim Posegga. Berlin : Springer, 2015. p. 201-215 (Lecture Notes in Computer Science; Vol. 8872).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Pieters W, Davarynejad M. Calculating Adversarial Risk from Attack Trees: Control Strength and Probabilistic Attackers. In Garcia-Alfaro J, Herrera-Joancomartí J, Lupu E, Posegga J, editors, Data Privacy Management, Autonomous Spontaneous Security, and Security Assurance: 9th International Workshop, DPM 2014, 7th International Workshop, SETOP 2014, and 3rd International Workshop, QASA 2014, Wroclaw, Poland, September 10-11, 2014. Revised Selected Papers. Berlin: Springer. 2015. p. 201-215. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-17016-9_13