The Use of Machine Learning in Digital Forensics: Review Paper
- DOI
- 10.2991/978-94-6463-110-4_9How to use a DOI?
- Keywords
- Digital Forensics; Machine learning Algorithms; Investigation; Digital Evidence; Swarm Intelligence
- Abstract
With the increase of cybercrimes in the current years, digital forensics has become an important matter to study in order achieve quality evidence. Forensic investigators face difficulties with data collection and analysis to reconstruct events. Due to humans’ immense interaction on a daily basis, machine learning allows investigators to perform more effective and efficient investigations using various algorithms. Machine learning is a subset of the artificial intelligence field. It is a scientific discipline focusing on developing computer models and algorithms that can perform specific tasks without programming, such as dataset training and testing, and it’s potential to aid in investigations. This paper reviews various machine learning techniques that examine and analyze digital evidence during the investigation process. Each machine learning algorithm works on a specific area of digital forensics based on the features, it overcomes complexity, data volume, time-lining, correlation, consistency, etc. moreover, this study compares machine learning algorithms in terms of standard criteria.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yusra Al Balushi AU - Hothefa Shaker AU - Basant Kumar PY - 2023 DA - 2023/01/30 TI - The Use of Machine Learning in Digital Forensics: Review Paper BT - Proceedings of the 1st International Conference on Innovation in Information Technology and Business (ICIITB 2022) PB - Atlantis Press SP - 96 EP - 113 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-110-4_9 DO - 10.2991/978-94-6463-110-4_9 ID - Balushi2023 ER -