- Volume 6 Issue 1
DOI QR Code
Digital Video Source Identification Using Sensor Pattern Noise with Morphology Filtering
모폴로지 필터링 기반 센서 패턴 노이즈를 이용한 디지털 동영상 획득 장치 판별 기술
- 이상형 (금오공과대학교 소프트웨어공학과) ;
- 김동현 (금오공과대학교 소프트웨어공학과) ;
- 오태우 (국가보안기술연구소) ;
- 김기범 (국가보안기술연구소) ;
- 이해연 (금오공과대학교 컴퓨터소프트웨어공학과)
- Received : 2016.01.06
- Accepted : 2016.07.05
- Published : 2017.01.31
With the advance of Internet Technology, various social network services are created and used by users. Especially, the use of smart devices makes that multimedia contents can be used and distributed on social network services. However, since the crime rate also is increased by users with illegal purposes, there are needs to protect contents and block illegal usage of contents with multimedia forensics. In this paper, we propose a multimedia forensic technique which is identifying the video source. First, the scheme to acquire the sensor pattern noise (SPN) using morphology filtering is presented, which comes from the imperfection of photon detector. Using this scheme, the SPN of reference videos from the reference device is estimated and the SPN of an unknown video is estimated. Then, the similarity between two SPNs is measured to identify whether the unknown video is acquired using the reference device. For the performance analysis of the proposed technique, 30 devices including DSLR camera, compact camera, camcorder, action cam and smart phone are tested and quantitatively analyzed. Based on the results, the proposed technique can achieve the 96% accuracy in identification.
Supported by : National Security Research Institute
- A. C. Popescu and H. Farid "Exposing digital forgeries in color filter array interpolated images," IEEE Transactions on Signal Processing, Vol.53, No.10, pp.3948-3959, Oct., 2005. https://doi.org/10.1109/TSP.2005.855406
- A. C. Popescu and H. Farid "Exposing Digital Forgeries by Detecting Traces of Re-sampling," IEEE Transactions on Signal Processing, Vol.53, No.2, pp.758-767, Feb., 2005. https://doi.org/10.1109/TSP.2004.839932
- J. Lukas, J. Fridrich, and M. Goljan "Detecting Digital Image Forgeries Using Sensor Pattern Noise," Proceedings of SPIE 6072, Security, Steganography, and Watermarking of Multimedia Contents VIII, Feb., 2006.
- M. Kirchner and T. Gloe, "On Resampling Detection in Recompressed Images," Proceedings of 1st IEEE International Workshop on Information Forensics and Security, pp.21-25, 2009.
- T. Gloe, M. Kirchner, A. Winkler, and R. Bohme, "Can We Trust Digital Image Forensics?," Proceedings of the 15th International Conference on Multimedia, pp.78-86, 2007.
- H. Farid, "Exposing Digital Forgeries in Scientific Images," Proceedings of the 8th Workshop on Multimedia and Security, pp.29-36, 2006.
- M. C. Stamm and K. J. Ray Liu, "Forensic Detection of Image Manipulation Using Statistical Intrinsic Fingerprints," IEEE Transactions on Information Forensics and Security, Vol.5, No.3, pp.492-506, 2010. https://doi.org/10.1109/TIFS.2010.2053202
- B. Mahdian and S. Saic, "Using Noise Inconsistencies for Blind Image Forensics," Image and Vision Computing, Vol.27, No.10, pp.1497-1503, 2009. https://doi.org/10.1016/j.imavis.2009.02.001
- J. Lukas, J. Fridrich, and M. Goljan, "Digital camera identification from sensor pattern noise," IEEE Transactions on Information Forensics Security, Vol.1, No.2, pp.205-214, Jun., 2006. https://doi.org/10.1109/TIFS.2006.873602
- M. Chen, J. Fridrich, and M. Goljan, "Source digital camcorder identification using ccd photo response non-uniformity," Proceedings of SPIE Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents IX, San Jose, CA, pp.1G-1H, 2007.