Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack

Nitin Naik; Paul Jenkins; Paul Grace; Shaligram Prajapat; Jingping Song; Jian Xu; Ricardo M. Czekster

doi:10.1007/978-3-031-47508-5_28

Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack

Nitin Naik
, Paul Jenkins
, Paul Grace
, Shaligram Prajapat
, Jingping Song
, Jian Xu
, Ricardo M. Czekster

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

As technology advances and AI becomes embedded and accepted into everyday life, the risk of cyberattacks by adversaries increases. These cyberattacks are ubiquitous affecting both businesses and individuals alike, and causing financial and reputational loss as a result. Numerous cyberattack analysis methods are available to analyse the risk of cyberattacks and offer the appropriate mitigation strategy. Nonetheless, several cyberattack analysis methods may not be effective and applicable in all cyberattack conditions due to several reasons such as their cost, complexity, resources and expertise. Therefore, this paper builds on an economical, simple and adaptable method for cyberattack analysis using an attack tree with weighted mean probability and risk of attack. It begins with an examination of a weighted mean approach followed by an investigation of the different types of weighted mean functions. Utilizing a series of orderly steps to perform a cyberattack analysis and assess its potential risk in an easy and effective manner. This method provides the means to calculate the potential risk of attack and therefore any mitigation that can be employed to minimise its effect.

Original language	English
Title of host publication	Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK
Editors	Nitin Naik, Paul Jenkins, Paul Grace, Longzhi Yang, Shaligram Prajapat
Pages	351-363
ISBN (Electronic)	9783031475085
DOIs	https://doi.org/10.1007/978-3-031-47508-5_28
Publication status	Published - 1 Feb 2024

Publication series

Name	Advances in Computational Intelligence Systems
Publisher	Springer
Volume	1453
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Keywords

cyberattack analysis
attack tree
Weighted mean risk of attack
Weighted mean probability of attack
information theft attack

Access to Document

10.1007/978-3-031-47508-5_28

Cite this

Naik, N., Jenkins, P., Grace, P., Prajapat, S., Song, J., Xu, J., & M. Czekster, R. (2024). Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack. In N. Naik, P. Jenkins, P. Grace, L. Yang, & S. Prajapat (Eds.), Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK (pp. 351-363). (Advances in Computational Intelligence Systems; Vol. 1453). https://doi.org/10.1007/978-3-031-47508-5_28

Naik, Nitin ; Jenkins, Paul ; Grace, Paul et al. / Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack. Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. editor / Nitin Naik ; Paul Jenkins ; Paul Grace ; Longzhi Yang ; Shaligram Prajapat. 2024. pp. 351-363 (Advances in Computational Intelligence Systems).

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abstract = "As technology advances and AI becomes embedded and accepted into everyday life, the risk of cyberattacks by adversaries increases. These cyberattacks are ubiquitous affecting both businesses and individuals alike, and causing financial and reputational loss as a result. Numerous cyberattack analysis methods are available to analyse the risk of cyberattacks and offer the appropriate mitigation strategy. Nonetheless, several cyberattack analysis methods may not be effective and applicable in all cyberattack conditions due to several reasons such as their cost, complexity, resources and expertise. Therefore, this paper builds on an economical, simple and adaptable method for cyberattack analysis using an attack tree with weighted mean probability and risk of attack. It begins with an examination of a weighted mean approach followed by an investigation of the different types of weighted mean functions. Utilizing a series of orderly steps to perform a cyberattack analysis and assess its potential risk in an easy and effective manner. This method provides the means to calculate the potential risk of attack and therefore any mitigation that can be employed to minimise its effect.",

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Naik, N, Jenkins, P, Grace, P, Prajapat, S, Song, J, Xu, J & M. Czekster, R 2024, Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack. in N Naik, P Jenkins, P Grace, L Yang & S Prajapat (eds), Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. Advances in Computational Intelligence Systems, vol. 1453, pp. 351-363. https://doi.org/10.1007/978-3-031-47508-5_28

Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack. / Naik, Nitin; Jenkins, Paul; Grace, Paul et al.
Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. ed. / Nitin Naik; Paul Jenkins; Paul Grace; Longzhi Yang; Shaligram Prajapat. 2024. p. 351-363 (Advances in Computational Intelligence Systems; Vol. 1453).

Research output: Chapter in Book/Published conference output › Conference publication

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AU - Naik, Nitin

AU - Jenkins, Paul

AU - Grace, Paul

AU - Prajapat, Shaligram

AU - Song, Jingping

AU - Xu, Jian

AU - M. Czekster, Ricardo

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AB - As technology advances and AI becomes embedded and accepted into everyday life, the risk of cyberattacks by adversaries increases. These cyberattacks are ubiquitous affecting both businesses and individuals alike, and causing financial and reputational loss as a result. Numerous cyberattack analysis methods are available to analyse the risk of cyberattacks and offer the appropriate mitigation strategy. Nonetheless, several cyberattack analysis methods may not be effective and applicable in all cyberattack conditions due to several reasons such as their cost, complexity, resources and expertise. Therefore, this paper builds on an economical, simple and adaptable method for cyberattack analysis using an attack tree with weighted mean probability and risk of attack. It begins with an examination of a weighted mean approach followed by an investigation of the different types of weighted mean functions. Utilizing a series of orderly steps to perform a cyberattack analysis and assess its potential risk in an easy and effective manner. This method provides the means to calculate the potential risk of attack and therefore any mitigation that can be employed to minimise its effect.

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Naik N, Jenkins P, Grace P, Prajapat S, Song J, Xu J et al. Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack. In Naik N, Jenkins P, Grace P, Yang L, Prajapat S, editors, Contributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK. 2024. p. 351-363. (Advances in Computational Intelligence Systems). Epub 2024 Jan 31. doi: 10.1007/978-3-031-47508-5_28

Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack

Abstract

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Keywords

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