Summary:
Digital camera of a smartphone is a component frequently used by people to capture a large number of videos, which can illustrate situations that compromise their presumption of innocence in court cases. Usually, these videos circulate on the Internet, prone to intentional manipulation to prosecute one person or exempt another. In this sense, digital videos are a matter of great importance for forensic science, because they can be useful to verify the authenticity of such evidence in judicial processes, helping to make sound decisions. However, it is possible that criminals or attackers know weaknesses of forensic techniques and use anti-forensic techniques to manipulate videos without leaving any trace of the procedure performed. Forensic science confronts anti-forensic techniques, analyzes them rigorously and applies anti-measures in the development of techniques to detect anti-forensic operations. In this paper, anti-forensic techniques are proposed to perform the source anonymization and forgery in MP4 videos.
Layman's summary:
Anti-forensic analysis, digital video, forensic analysis, PRNU, sensor noise, source identification, video anonymization, vide forgery, video metadata, wavelet transform.
Keywords: Anti-forensic analysis, digital video, forensic analysis, PRNU, sensor noise, source identification, video anonymization, vide forgery, video metadata, wavelet transform.
JCR Impact Factor and WoS quartile: 3,745 - Q1 (2019); 3,900 - Q2 (2022)
DOI reference:
https://doi.org/10.1109/ACCESS.2019.2949839
Published on paper: 2019.
Published on-line: October 2019.
Citation:
A.L. Sandoval Orozco, C. Quinto Huamán, J. Cifuentes, L.J. García Villalba, Digital video source acquisition forgery technique based on pattern sensor noise extraction. IEEE Access. Vol. 7, pp. 157363 - 157373, 2019. [Online: October 2019]
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