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Published on 15 May 2025
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Huang,Y. (2025). Application of Digital Forensics in Cybercrime Investigations. Applied and Computational Engineering,151,69-74.
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Application of Digital Forensics in Cybercrime Investigations

Yitai Huang *,1,
  • 1 Changchun University of Technology, Changchun, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/2025.22847

Abstract

As cybercrime continues to pose significant threats to individuals, businesses, and national security, digital forensics has become an important tool for investigating cybercrime. This article explores the application of digital forensics technology, with a focus on disk forensics, memory forensics, and network forensics. It provides an overview of common forensic techniques, including key forensic methods, their advantages, limitations, and real-world applications. This study emphasizes the latest advancements in forensic tools and technologies, including AI-driven automation and machine learning-based anomaly detection, highlighting their role in recovering digital evidence, identifying cybercrime activities, and supporting legal proceedings. However, despite these advancements, challenges such as encrypted data, anti-forensic techniques, and increasingly complex network threats were also discussed. These findings emphasize the necessity of standardized forensic protocols, the integration of AI-driven automation, and improved forensic methods to enhance investigation efficiency and ensure the integrity and reliability of digital evidence in the legal environment.

Keywords

Digital Forensics, Cybercrime Investigation, Disk Forensics, Memory Forensics, Network Forensics

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Cite this article

Huang,Y. (2025). Application of Digital Forensics in Cybercrime Investigations. Applied and Computational Engineering,151,69-74.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 3rd International Conference on Software Engineering and Machine Learning

Conference website: https://2025.confseml.org/
ISBN:978-1-80590-091-7(Print) / 978-1-80590-092-4(Online)
Conference date: 2 July 2025
Editor:Marwan Omar
Series: Applied and Computational Engineering
Volume number: Vol.151
ISSN:2755-2721(Print) / 2755-273X(Online)

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