Paper
27 February 2007 Detection of malevolent changes in digital video for forensic applications
Author Affiliations +
Abstract
In this paper we present a new method for the detection of forgeries in digital videos, using the sensor's pattern noise. The camera pattern noise is a unique stochastic high frequency characteristic of imaging sensors and the detection of a forged frame in a video is determined by comparing the correlation between the noise within the frame itself and the reference pattern noise with an empirical threshold. The reference pattern is created for the identification of the camera and the authentication of the video too. Such a pattern is defined as self building because it is created from the video sequence during the time develop, with a technique applied frame per frame, by averaging the noise extracted from each frame. The method has been inherited from an existing system created by Fridrich et al.1 for still images. By using this method we are able to identify if all the scenes of a video sequence have been taken with the same camera and if the number and/or the content of the frames of the video have been modified. A large section of the paper is dedicated to the experimental results, where we demonstrate that it is possible to perform a reliable identification even from video that has undergone MPEG compression or frame interpolation.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
N. Mondaini, R. Caldelli, A. Piva, M. Barni, and V. Cappellini "Detection of malevolent changes in digital video for forensic applications", Proc. SPIE 6505, Security, Steganography, and Watermarking of Multimedia Contents IX, 65050T (27 February 2007); https://doi.org/10.1117/12.704924
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Cited by 53 scholarly publications.
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KEYWORDS
Video

Cameras

Video compression

Sensors

Imaging systems

Image processing

Forensic science

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