EXTENDING AUTOPSY TOOL WITH OBJECT DETECTION MODULE

Authors

  • Исидора Кнежевић Autor

DOI:

https://doi.org/10.24867/33BE11Knezevic

Keywords:

digital forensics, object detection, YOLOv8

Abstract

Digital forensics faces the challenge of analyzing large collections of phоtographs that may contain key evidence in a criminal investigation. This paper presents a solution, module for the Autopsy tool, “Weapon and Money Detector”, which uses the YOLOv8 deep learning model to detect objects such as guns, knives, banknotes and credit cards, significantly speeding up the analysis process. The proposed solution shows significantly better performance in object detection compared to existing solutions.

References

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[6]"Autopsy Forensic Browser Developer's Guide and API Reference," [Online]. Available: http://sleuthkit.org/autopsy/docs/api-docs/4.21.0//. [Accessed 10 December 2024].

[7] J. Murel and E. Kavlakoglu, "What is object detection?" IBM, 3 January 2024. [Online]. Available: https://www.ibm.com/think/topics/object-detection. [Accessed 12 December 2024].

[8] N. Bilous, V. Malko, M. Frohme and A. Nechyporenko, "Comparison of CNN-Based Architectures for Detection of Different Object Classes," AI, vol. 5, pp. 2300-2320, 2024.

[9] F. Pérez-Hernández, S. Tabik, A. Lamas, R. Olmos, H. Fujita and F. Herrera, "Object Detection Binary Classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance," Knowledge-Based Systems, vol. 194, no. 105590, 2020.

Published

2026-01-30

Issue

Section

Electrotechnical and Computer Engineering