Since the past few years, the complexity and heterogeneity of digital crimes has increased exponentially, which has made the digital evidence & digital forensics paramount for both criminal investigation and civil litigation cases. Some of the routine digital forensic analysis tasks are cumbersome and can increase the number of pending cases especially when there is a shortage of domain experts. While the work is not very complex, the sheer scale can be taxing. With the current scenarios and future predictions, crimes are only going to become more complex and the precedent of collecting and examining digital evidence is only going to increase. In this research, we propose an ML based Digital Forensics Software for Triage Analysis called Synthetic Forensic Omnituens (SynFO) that can automate evidence acquisition, extraction of relevant files, perform automated triage analysis and generate a basic report for the analyst. Results of this research show a promising future for automation with the help of Machine Learning.
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Gogia, Gaurav and Rughani, Parag H.
"AN ML BASED DIGITAL FORENSICS SOFTWARE FOR TRIAGE ANALYSIS THROUGH FACE RECOGNITION,"
Journal of Digital Forensics, Security and Law: Vol. 17
, Article 6.
Available at: https://commons.erau.edu/jdfsl/vol17/iss2/6