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Proceedings Paper

Countering anti-forensics by means of data fusion
Author(s): Marco Fontani; Alessandro Bonchi; Alessandro Piva; Mauro Barni
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Paper Abstract

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.

Paper Details

Date Published: 19 February 2014
PDF: 15 pages
Proc. SPIE 9028, Media Watermarking, Security, and Forensics 2014, 90280Z (19 February 2014); doi: 10.1117/12.2039569
Show Author Affiliations
Marco Fontani, CNIT, Univ. degli Studi di Siena (Italy)
Alessandro Bonchi, Univ. degli Studi di Firenze (Italy)
Alessandro Piva, Univ. degli Studi di Firenze (Italy)
Mauro Barni, Univ. degli Studi di Siena (Italy)


Published in SPIE Proceedings Vol. 9028:
Media Watermarking, Security, and Forensics 2014
Adnan M. Alattar; Nasir D. Memon; Chad D. Heitzenrater, Editor(s)

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