An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions

Wissal Mestour; Niek Jan van den Hout; Jan Treur; Peter H.M.P. Roelofsma

doi:10.1007/978-3-031-88705-5_32

An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions

Wissal Mestour, Niek Jan van den Hout, Jan Treur^*, Peter H.M.P. Roelofsma

^*Corresponding author for this work

Artificial Intelligence

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

This study investigates cybersecurity threats in financial organizations by developing an adaptive network model to mitigate attacks. Using the cyber kill chain framework, the performed simulations reveal the adaptive dynamics between attackers and defenders over time. In the first scenario, the attacker’s rapid learning leads to successful attacks and data breaches. In the second scenario, the organization’s superior learning results in effective defenses, with no data stolen. The findings underscore the importance of continuous learning and adaptive defense mechanisms in cybersecurity.

Original language	English
Title of host publication	Intelligent Human Computer Interaction
Subtitle of host publication	16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I
Editors	Dhananjay Singh, Jan-Willem van ’t Klooster, Uma Shanker Tiwary
Publisher	Springer Nature
Pages	380-395
Number of pages	16
Volume	1
ISBN (Electronic)	9783031887055
ISBN (Print)	9783031887048
DOIs	https://doi.org/10.1007/978-3-031-88705-5_32
Publication status	Published - 2025
Event	16th International Conference on Intelligent Human Computer Interaction, IHCI 2024 - Twente, Netherlands Duration: 13 Nov 2024 → 16 Nov 2024

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	15557 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	IHCI: International Conference on Intelligent Human Computer Interaction
Publisher	Springer
Volume	2024

Conference

Conference	16th International Conference on Intelligent Human Computer Interaction, IHCI 2024
Country/Territory	Netherlands
City	Twente
Period	13/11/24 → 16/11/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

Adaptive network
cyber security
cyber threats
financial institutions
risk assessment
What-If analysis

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10.1007/978-3-031-88705-5_32

An Adaptive Network Model to Analyse Cyber SecurityFinal published version, 2.41 MBLicence: Article 25fa Dutch Copyright Act

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Mestour, W., van den Hout, N. J., Treur, J., & Roelofsma, P. H. M. P. (2025). An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions. In D. Singh, J.-W. van ’t Klooster, & U. S. Tiwary (Eds.), Intelligent Human Computer Interaction: 16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I (Vol. 1, pp. 380-395). (Lecture Notes in Computer Science; Vol. 15557 LNCS), (IHCI: International Conference on Intelligent Human Computer Interaction; Vol. 2024). Springer Nature. https://doi.org/10.1007/978-3-031-88705-5_32

Mestour, Wissal ; van den Hout, Niek Jan ; Treur, Jan et al. / An Adaptive Network Model to Analyse Cyber Security : Understanding Cyber Threats in Financial Institutions. Intelligent Human Computer Interaction: 16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I. editor / Dhananjay Singh ; Jan-Willem van ’t Klooster ; Uma Shanker Tiwary. Vol. 1 Springer Nature, 2025. pp. 380-395 (Lecture Notes in Computer Science). (IHCI: International Conference on Intelligent Human Computer Interaction).

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title = "An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions",

abstract = "This study investigates cybersecurity threats in financial organizations by developing an adaptive network model to mitigate attacks. Using the cyber kill chain framework, the performed simulations reveal the adaptive dynamics between attackers and defenders over time. In the first scenario, the attacker{\textquoteright}s rapid learning leads to successful attacks and data breaches. In the second scenario, the organization{\textquoteright}s superior learning results in effective defenses, with no data stolen. The findings underscore the importance of continuous learning and adaptive defense mechanisms in cybersecurity.",

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author = "Wissal Mestour and \{van den Hout\}, \{Niek Jan\} and Jan Treur and Roelofsma, \{Peter H.M.P.\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 16th International Conference on Intelligent Human Computer Interaction, IHCI 2024 ; Conference date: 13-11-2024 Through 16-11-2024",

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Mestour, W, van den Hout, NJ, Treur, J & Roelofsma, PHMP 2025, An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions. in D Singh, J-W van ’t Klooster & US Tiwary (eds), Intelligent Human Computer Interaction: 16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I. vol. 1, Lecture Notes in Computer Science, vol. 15557 LNCS, IHCI: International Conference on Intelligent Human Computer Interaction, vol. 2024, Springer Nature, pp. 380-395, 16th International Conference on Intelligent Human Computer Interaction, IHCI 2024, Twente, Netherlands, 13/11/24. https://doi.org/10.1007/978-3-031-88705-5_32

An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions. / Mestour, Wissal; van den Hout, Niek Jan; Treur, Jan et al.
Intelligent Human Computer Interaction: 16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I. ed. / Dhananjay Singh; Jan-Willem van ’t Klooster; Uma Shanker Tiwary. Vol. 1 Springer Nature, 2025. p. 380-395 (Lecture Notes in Computer Science; Vol. 15557 LNCS), (IHCI: International Conference on Intelligent Human Computer Interaction; Vol. 2024).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AB - This study investigates cybersecurity threats in financial organizations by developing an adaptive network model to mitigate attacks. Using the cyber kill chain framework, the performed simulations reveal the adaptive dynamics between attackers and defenders over time. In the first scenario, the attacker’s rapid learning leads to successful attacks and data breaches. In the second scenario, the organization’s superior learning results in effective defenses, with no data stolen. The findings underscore the importance of continuous learning and adaptive defense mechanisms in cybersecurity.

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Mestour W, van den Hout NJ, Treur J, Roelofsma PHMP. An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions. In Singh D, van ’t Klooster JW, Tiwary US, editors, Intelligent Human Computer Interaction: 16th International Conference, IHCI 2024, Twente, The Netherlands, November 13–16, 2024, Revised Selected Papers, Part I. Vol. 1. Springer Nature. 2025. p. 380-395. (Lecture Notes in Computer Science). (IHCI: International Conference on Intelligent Human Computer Interaction). Epub 2025 May 29. doi: 10.1007/978-3-031-88705-5_32

An Adaptive Network Model to Analyse Cyber Security: Understanding Cyber Threats in Financial Institutions

Abstract

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