Broken Integrity Detection of Video Files in Video Event Data Recorders

As digital evidence has a highly influential role in proving the innocence of suspects, methods for integrity verification of such digital evidence have become essential in the digital forensic field. Most surveillance camera systems are not equipped with proper built-in integrity protection functions. Because digital forgery techniques are becoming increasingly sophisticated, manually determining whether digital content has been falsified is becoming extremely difficult for investigators. Hence, systematic approaches to forensic integrity verification are essential for ascertaining truth or falsehood. We propose an integrity determination method that utilizes the structure of the video content in a Video Event Data Recorder (VEDR). The proposed method identifies the difference in frame index fields between a forged file and an original file. Experiments conducted using real VEDRs in the market and video files forged by a video editing tool demonstrate that the proposed integrity verification scheme can detect broken integrity in video content.

[1]  S. Kong,et al.  Frame-Based Recovery of Corrupted Video Files Using Video Codec Specifications , 2014, IEEE Transactions on Image Processing.

[2]  Simson L. Garfinkel,et al.  Hash-based carving: Searching media for complete files and file fragments with sector hashing and hashdb , 2015, Digit. Investig..

[3]  Shivi Sharma,et al.  Survey on Digital Video Watermarking Techniques , 2016 .

[4]  Simon Tjoa,et al.  Forensics Investigations of Multimedia Data: A Review of the State-of-the-Art , 2011, 2011 Sixth International Conference on IT Security Incident Management and IT Forensics.

[5]  Rahul Sukthankar,et al.  Forensic video reconstruction , 2004, VSSN '04.

[6]  Vrizlynn L. L. Thing,et al.  Design of a Digital Forensics Evidence Reconstruction System for Complex and Obscure Fragmented File Carving , 2011, 2011 Seventh International Conference on Computational Intelligence and Security.

[7]  Simon Tjoa,et al.  Roadmap to Approaches for Carving of Fragmented Multimedia Files , 2011, 2011 Sixth International Conference on Availability, Reliability and Security.

[8]  Chia-Wen Lin,et al.  Video forgery detection using correlation of noise residue , 2008, 2008 IEEE 10th Workshop on Multimedia Signal Processing.

[9]  Heejo Lee,et al.  Comments on the Linux FAT32 allocator and file creation order reconstruction [Digit Investig 11(4), 224-233] , 2015, Digit. Investig..

[10]  David Billard,et al.  Making sense of unstructured flash-memory dumps , 2010, SAC '10.

[11]  Eoghan Casey Bs Ma.  Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet , 2000 .

[12]  Ki-Young Kim,et al.  Data forgery detection for vehicle black box , 2014, 2014 International Conference on Information and Communication Technology Convergence (ICTC).

[13]  P. Y. A. Ryan.  Towards an Engineering Approach to Component Adaptation , 2006 .

[14]  Wicher Minnaard.  The Linux FAT32 allocator and file creation order reconstruction , 2014, Digit. Investig..

[15]  Weihong Wang,et al.  Exposing digital forgeries in video by detecting duplication , 2007, MM&Sec.

[16]  Heejo Lee,et al.  Integrity Verification Scheme of Video Contents in Surveillance Cameras for Digital Forensic Investigations , 2015, IEICE Trans. Inf. Syst..