19 February 2014 Countering anti-forensics by means of data fusion
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In the last years many image forensic (IF) algorithms have been proposed to reveal traces of processing or tampering. On the other hand, Anti-Forensic (AF) tools have also been developed to help the forger in removing editing footprints. Inspired by the fact that it is much harder to commit a perfect crime when the forensic analyst uses a multi-clue investigation strategy, we analyse the possibility o ered by the adoption of a data fusion framework in a Counter-Anti-Forensic (CAF) scenario. We do so by adopting a theoretical framework, based on Dempster-Shafer Theory of Evidence, to synergically merge information provided by IF tools and CAF tools, whose goal is to reveal traces introduced by anti-forensic algorithms. The proposed system accounts for the non-trivial relationships between IF and CAF techniques; for example, in some cases the outputs from the former are expected to contradict the output from the latter. We evaluate the proposed method within a representative forensic task, that is splicing detection in JPEG images, with the forger trying to conceal traces using two di erent counter-forensic methods. Results show that decision fusion strongly limits the e ectiveness of AF methods.
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Marco Fontani, Marco Fontani, Alessandro Bonchi, Alessandro Bonchi, Alessandro Piva, Alessandro Piva, Mauro Barni, Mauro Barni, } "Countering anti-forensics by means of data fusion", Proc. SPIE 9028, Media Watermarking, Security, and Forensics 2014, 90280Z (19 February 2014); doi: 10.1117/12.2039569; https://doi.org/10.1117/12.2039569

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