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.

Second-Order Statistics Analysis to Cope With Contrast Enhancement Counter-Forensics / A. De Rosa; M. Fontani; M. Massai; A. Piva; M. Barni. - In: IEEE SIGNAL PROCESSING LETTERS. - ISSN 1070-9908. - ELETTRONICO. - 22:(2015), pp. 1132-1136. [10.1109/LSP.2015.2389241]

Second-Order Statistics Analysis to Cope With Contrast Enhancement Counter-Forensics

DE ROSA, ALESSIA;FONTANI, MARCO;PIVA, ALESSANDRO;
2015

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
22
1132
1136
A. De Rosa; M. Fontani; M. Massai; A. Piva; M. Barni
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/960456
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