Research Article
A Survey on the Development of Machine Learning and Artificial Intelligence Techniques in Digital Forensics
@INPROCEEDINGS{10.1007/978-3-032-05832-4_16, author={Alia Ahli and Ayesha Farah Raza and Ines Camarata and Khalil Al-Hussaeni}, title={A Survey on the Development of Machine Learning and Artificial Intelligence Techniques in Digital Forensics}, proceedings={Safe, Secure, Ethical, Responsible Technologies and Emerging Applications. Second EAI International Conference, SAFER-TEA 2024, Dubai, United Arab Emirates, December 9--10, 2024, Proceedings}, proceedings_a={SAFER-TEA}, year={2026}, month={11}, keywords={Digital Forensics Machine Learning AI}, doi={10.1007/978-3-032-05832-4_16} }- Alia Ahli
Ayesha Farah Raza
Ines Camarata
Khalil Al-Hussaeni
Year: 2026
A Survey on the Development of Machine Learning and Artificial Intelligence Techniques in Digital Forensics
SAFER-TEA
Springer
DOI: 10.1007/978-3-032-05832-4_16
Abstract
With the increasing popularity of Artificial Intelligence (AI) and Machine Learning (ML), several studies have utilized AI and ML techniques to enhance the digital evidence analysis processes and obtain accurate results with less time and effort. This paper surveys the current research efforts concerned with applying AI and ML techniques into the fields of digital forensics, and provides a comprehensive overview and insightful comparisons of relevant works across different sub-disciplines. All surveyed works were evaluated using traditional quantitative metrics, such as accuracy and F1 score, and the qualitative international standard on digital evidence interpretation ISO/IEC 27042, which provides a bird’s eye view on interpretability, a realistic expectation of a proposed forensic analysis method. Our findings indicate that several existing works fall short from satisfying all the metrics of the ISO/IEC standard.