Explainable Artificial Intelligence in Malware Analysis and Forensics

Alshraá AS, Dibaei Asl M, Muhammad M, German R (2026)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2026

Publisher: wiley

Edited Volumes: Attacks and Defenses in Explainable Artificial Intelligence

ISBN: 9781394305612

DOI: 10.1002/9781394305612.ch16

Abstract

Using explainable artificial intelligence (XAI) techniques in malware analysis and digital forensics shows promise for transforming cybersecurity practices. This paper examines the role of XAI in providing understandable insights into malware behavior and characteristics, addressing the limitations of traditional approaches, and improving threat detection capabilities. By using interpretable machine learning models and analyzing feature importance, XAI allows security analysts to comprehend the reasoning behind automated decisions and prioritize response efforts accordingly. Real-world case studies demonstrate the effectiveness of XAI in recognizing and mitigating cyber threats, while ethical considerations emphasize the necessity of responsible and transparent use of XAI in cybersecurity practices. Looking ahead, future directions and emerging trends in real-time XAI applications, hybrid approaches, and interdisciplinary collaboration present exciting opportunities for advancing the field of XAI-driven malware analysis and digital forensics.

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How to cite

APA:

Alshraá, A.S., Dibaei Asl, M., Muhammad, M., & German, R. (2026). Explainable Artificial Intelligence in Malware Analysis and Forensics. In Amol Dattatraya Vibhute, Rajesh Kumar Dhanaraj, Malathy Sathyamoorthy, A. Paramasivam (Eds.), Attacks and Defenses in Explainable Artificial Intelligence. wiley.

MLA:

Alshraá, Abdullah S., et al. "Explainable Artificial Intelligence in Malware Analysis and Forensics." Attacks and Defenses in Explainable Artificial Intelligence. Ed. Amol Dattatraya Vibhute, Rajesh Kumar Dhanaraj, Malathy Sathyamoorthy, A. Paramasivam, wiley, 2026.

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