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A fast source camera identification and verification method based on PRNU analysis for use in video forensic investigations

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Abstract

Due to the rapid development of digital and cloud technologies, everyone can easily shoot and spread digital videos via email or social media. However, it is difficult for law enforcement to trace the origin of those digital videos, while some videos or images containing illegal information such as personal privacy, obscene pornography, and national security-related content. Recently, a significant breakthrough is achieved by using Photo-Response Non-Uniformity (PRNU) noise to characterize the camera sensor. However, PRNU analysis is often carried out on a frame-by-frame basis. As a result, the processing time is unbearable when treating a large set of videos and devices. In this paper, we propose a novel video forensic method considering both cameras rolling and I-frame of videos to improve the processing time and accuracy. Experimental results demonstrate that our proposed method is at a minimum of 15 times on average faster than the most wildly used method, PRNU analysis, and reduce the false positive rate as compared to existing methods used in the field of the forensic examination.

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Notes

  1. Rolling is defined as the rotation around the optical axis of the camera.

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Acknowledgments

This work on this paper was supported by the National Science Council, Taiwan, Republic of China (MOST 107-2221-E-015-003-MY2, MOST 109-2221-E-015-002-).

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Authors and Affiliations

  1. Department of Forensic Science, Central Police University, Taoyuan City, Taiwan, Republic of China

    Wen-Chao Yang

  2. Electrical and Computer Engineering Department, Old Dominion University, Norfolk, VA, USA

    Jiajun Jiang & Chung-Hao Chen

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  1. Wen-Chao Yang
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  2. Jiajun Jiang
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  3. Chung-Hao Chen
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Correspondence to Wen-Chao Yang.

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Appendix

Appendix

Some I-frames of the videos used for training and testing in the experiments are shown in this appendix. Figs. 5 and  6 show 2 I-frames of 8 testing videos and 8 testing videos, respectively. It is worth noting that there exist the similar scenes and colors in videos from different portable devices in both Figs. 5 and 6.

Fig. 5
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Some I-frames of the training videos in the experiments

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Fig. 6
figure 6figure 6

Some I-frames of the testing videos in the experiments

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Yang, WC., Jiang, J. & Chen, CH. A fast source camera identification and verification method based on PRNU analysis for use in video forensic investigations. Multimed Tools Appl 80, 6617–6638 (2021). https://doi.org/10.1007/s11042-020-09763-z

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  • DOI: https://doi.org/10.1007/s11042-020-09763-z

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