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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Novel Method for Detecting Double Compressed Facebook JPEG Images
verfasst von : Allan NG, Lei Pan, Yang Xiang
Erschienen in: Applications and Techniques in Information Security
Verlag: Springer Berlin Heidelberg
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Images published on online social sites such as Facebook are increasingly prone to be misused for malicious purposes. However, existing image forensic research assumes that the investigator can confiscate every piece of evidence and hence overlooks the fact that the original image is difficult to obtain. Because Facebook applies a Discrete Cosine Transform (DCT)-based compression on uploaded images, we are able to detect the modified images which are re-uploaded to Facebook. Specifically, we propose a novel method to effectively detect the presence of double compression via the spatial domain of the image: We select small image patches from a given image, define a distance metric to measure the differences between compressed images, and propose an algorithm to infer whether the given image is double compressed without referring to the original image. To demonstrate the correctness of our algorithm, we correctly predict the number of compressions being applied to a Facebook image.