Neural Networks in Digital Forensics: A Decadal Exploration

Abstract

This dataset, retrieved from Lens.org through meticulous keyword searches, delves into the intricate domain of digital forensics intersecting with neural networks, specifically focusing on internet-related contexts. A total of 476 journal articles from the period 2002-2012 were scrutinized. The research pinpointed the nexus of digital forensics, internet studies, and neural networks, uncovering 87 articles at the intersection of law and technology. Noteworthy findings include prolific institutions like the University of Cambridge and University of Oxford, each contributing significantly to this niche. The dataset emphasizes the rise in publications during 2009 and 2012, underlining crucial developments in this interdisciplinary field. David Farrington emerged as the most prolific author, leaving a notable imprint with 70 publications. The dataset also spotlighted a seminal work titled "An automated timeline reconstruction approach for digital forensic investigations," published in 2016, representing a paradigm shift in the field. The dataset's emphasis on neural networks within digital forensics, coupled with its geographic focus on the United Kingdom and Australia, makes it a pivotal resource for researchers exploring the convergence of law, technology, and cyber investigations.

Highlights:

• Interdisciplinary Nexus: Explores the intersection of digital forensics, neural networks, and internet studies.
• Prolific Institutions: Identifies leading contributors such as University of Cambridge and University of Oxford.
• Geographic Focus: Emphasizes key research from the United Kingdom and Australia in the realm of digital forensics and law.

Keywords: Digital Forensics, Neural Networks, Internet Studies, Law, Cyber Investigations