Image forensic analysis for the detection of contrast enhancement and other histogram-based processing, usually relies on the study of first-order statistics derived from image histogram. Methods based on such an approach, though, are easily circumvented by adopting some counter-forensic attacks. To overcome such a problem, we propose a novel forensic technique based on the study of second-order statistics derived from the co-occurrence matrix. The experiments we carried out demonstrate that the proposed approach is very effective even in the presence of counter-forensic attacks, while it retains the good performance of histogram-based methods when no attack is present.

De Rosa, A., Fontani, M., Massai, M., Piva, A., Barni, M. (2015). Second-order Statistics Analysis to Cope with Contrast Enhancement Counter-Forensics. IEEE SIGNAL PROCESSING LETTERS, 22(8), 1132-1136 [10.1109/LSP.2015.2389241].

Second-order Statistics Analysis to Cope with Contrast Enhancement Counter-Forensics

Barni, M.
2015-01-01

Abstract

Image forensic analysis for the detection of contrast enhancement and other histogram-based processing, usually relies on the study of first-order statistics derived from image histogram. Methods based on such an approach, though, are easily circumvented by adopting some counter-forensic attacks. To overcome such a problem, we propose a novel forensic technique based on the study of second-order statistics derived from the co-occurrence matrix. The experiments we carried out demonstrate that the proposed approach is very effective even in the presence of counter-forensic attacks, while it retains the good performance of histogram-based methods when no attack is present.
2015
De Rosa, A., Fontani, M., Massai, M., Piva, A., Barni, M. (2015). Second-order Statistics Analysis to Cope with Contrast Enhancement Counter-Forensics. IEEE SIGNAL PROCESSING LETTERS, 22(8), 1132-1136 [10.1109/LSP.2015.2389241].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/981785