Semantic Video Carving Using Perceptual Hashing and Optical Flow
Video files are frequently encountered in digital forensic investigations. However, these files are usually fragmented and are not stored consecutively on physical media. Suspects may logically delete the files and also erase filesystem information. Unlike image carving, limited research has focused on video carving. Current approaches depend on filesystem information or attempt to match every pair of fragments, which is impractical. This chapter proposes a two-stage approach to tackle the problem. The first perceptual grouping stage computes a hash value for each fragment; the Hamming distance between hashes is used to quickly group fragments from the same file. The second precise stitching stage uses optical flow to identify the correct order of fragments in each group. Experiments with the BOSS dataset reveal that the approach is very fast and does not sacrifice accuracy or overall precision.
KeywordsDigital forensics Video carving Perceptual hashing Optical flow
Unable to display preview. Download preview PDF.
- Ali, S., Shah, M.: A Lagrangian particle dynamics approach for crowd flow segmentation and stability analysis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2007)Google Scholar
- BOSS Project, BOSS Dataset (2012). www.multitel.be/BOSS
- CAVIAR Project, CAVIAR: Context Aware Vision using Image-Based Active Recognition, School of Informatics, University of Edinburgh, Edinburgh, United Kingdom (2017). homepages.inf.ed.ac.uk/rbf/CAVIAR
- International Organization for Standardization, Information Technology – Coding of Audio-Visual Objects – Part 2: Visual, ISO/IEC Standard 14496-2:2004, Geneva, Switzerland (2004)Google Scholar
- International Organization for Standardization, Information Technology – Coding of Audio-Visual Objects – Part 10: Advanced Video Coding, ISO/IEC Standard 14496-10:2010, Geneva, Switzerland (2010)Google Scholar
- Lewis, A.: Reconstructing Compressed Photo and Video Data, Technical Report No. 813, UCAM-CL-TR-813, Computer Laboratory, University of Cambridge, Cambridge, United Kingdom (2012)Google Scholar
- Neelima, A., Singh, K.: A short survey of perceptual hash functions. ADBU Journal of Engineering Technology 1 (2014)Google Scholar
- Poisel, R., Tjoa, S.: Roadmap to approaches for carving of fragmented multimedia files. In: Proceedings of the Sixth International Conference on Availability, Reliability and Security, pp. 752–757 (2011)Google Scholar
- Poisel, R., Tjoa, S.: A comprehensive literature review of file carving. In: Proceedings of the Eighth International Conference on Availability, Reliability and Security, pp. 475–484 (2013)Google Scholar
- Poisel, R., Tjoa, S., Tavolato, P.: Advanced file carving approaches for multimedia files. Journal of Wireless Mobile Networks, Ubiquitous Computing and Dependable Applications 2(4), 42–58 (2011)Google Scholar
- Richard, G., Roussev, V.: Scalpel: a frugal, high performance file carver. In: Proceedings of the Digital Forensic Research Workshop (2005)Google Scholar