Applications of Machine Learning in Digital Forensics
Sana Qadir, Basirah Noor
Abstract
Digital forensics (DF) has become a substantial process to perform in depth investigations. But due to the digitalization, the potential Data volumes are increasing and hence it has become difficult to analyze them. Machine Learning (ML) is a panacea in this regard. It not only facilitates the analysis process but also yields accurate results. Therefore, with a focus on DF, this paper surveys a wide range of publications mentioning ML based techniques that can be used to ease the process of DF principally in the field of malware, network forensics, image/video forensics, and mobile/memory forensics. The results of the review show that ML is a fast and reliable procedure and needs to be explored more actively, particularly in DF field. The results are also used to develop a conceptual framework for a general procedure of ML based Digital Forensics.