A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response

Dunsin, Dipo, Ghanem, Mohamed Chahine, Ouazzane, Karim and Vassilev, Vassil (2024) A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response. Forensic Science International: Digital Investigation, 48 (301675). pp. 1-22. ISSN 2666-2817

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Abstract / Description

In the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised to amplify the efficiency and precision of digital forensics investigations. However, the use of ML and AI in digital forensics is still in its nascent stages. As a result, this paper gives a thorough and in-depth analysis that goes beyond a simple survey and review. The goal is to look closely at how AI and ML techniques are used in digital forensics and incident response. This research explores cutting-edge research initiatives that cross domains such as data collection and recovery, the intricate reconstruction of cybercrime timelines, robust big data analysis, pattern recognition, safeguarding the chain of custody, and orchestrating responsive strategies to hacking incidents. This endeavour digs far beneath the surface to unearth the intricate ways AI-driven methodologies are shaping these crucial facets of digital forensics practice. While the promise of AI in digital forensics is evident, the challenges arising from increasing database sizes and evolving criminal tactics necessitate ongoing collaborative research and refinement within the digital forensics profession. This study examines the contributions, limitations, and gaps in the existing research, shedding light on the potential and limitations of AI and ML techniques. By exploring these different research areas, we highlight the critical need for strategic planning, continual research, and development to unlock AI's full potential in digital forensics and incident response. Ultimately, this paper underscores the significance of AI and ML integration in digital forensics, offering insights into their benefits, drawbacks, and broader implications for tackling modern cyber threats.

Item Type: Article
Uncontrolled Keywords: Data Collection and Recovery, Cybercrime Investigation, Artificial Intelligence, Pattern Recognition, Big Data Analysis, Machine Learning, Chain of Custody, Volatile Memory, Digital Forensic, Cyber Incident, DFIR
Subjects: 000 Computer science, information & general works
300 Social sciences > 360 Social problems & services; associations
Department: School of Computing and Digital Media
Depositing User: Dipo Dunsin
Date Deposited: 23 Nov 2023 13:11
Last Modified: 31 Jan 2024 09:42
URI: https://repository.londonmet.ac.uk/id/eprint/8914

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