Optimizing the Cyber Crisis Management Process with an Artificial Intelligence Approach in Iranian Banks

Authors

  • Samira AzadSanjari * Department of Industries, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.
  • Seyed Kamal Charsoughi Department of Industries, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.

https://doi.org/10.48314/apem.vi.38

Abstract

Given the increasing frequency and complexity of cyber-attacks in recent years, leveraging Artificial Intelligence (AI) to enhance Cyber Crisis Management (CCM) has become a necessity. According to various cybersecurity reports, banking malware and financial fraud have experienced significant growth over the past decades. In light of the escalating sophistication of cyber threats and the rapid emergence of new attack vectors, traditional crisis management methods are no longer sufficient to meet the security demands of Iranian banking institutions. In this research, we propose an optimized AI-driven framework for CCM. In our proposed approach, AI is employed in the pre-crisis phase to predict complex cyber threats, allowing for the rapid deployment of defensive measures that minimize the likelihood of a crisis. During the crisis itself, AI enhances the Incident Response (IR) process through advanced automated algorithms capable of analyzing vast volumes of data in minimal time. The integration of AI into the CCM process facilitates faster response times, process automation, reduction of human error, real-time analysis of high-volume and complex datasets, and enables continuous learning and adaptive improvement.

Keywords:

Artificial intelligence, Cyber crisis management, Electronic banking, Cybersecurity, Threat detection, Incident response, Vulnerability assessment

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Published

2025-08-19

Issue

Articles in Press

Section

Articles

How to Cite

Optimizing the Cyber Crisis Management Process with an Artificial Intelligence Approach in Iranian Banks. (2025). Annals of Process Engineering and Management. https://doi.org/10.48314/apem.vi.38

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