DocumentCode :
8998
Title :
Second-Order Statistics Analysis to Cope With Contrast Enhancement Counter-Forensics
Author :
De Rosa, Alessia ; Fontani, Marco ; Massai, Matteo ; Piva, Alessandro ; Barni, Mauro
Author_Institution :
Dept. of Inf. Eng., Univ. di Firenze, Florence, Italy
Volume :
22
Issue :
8
fYear :
2015
fDate :
Aug. 2015
Firstpage :
1132
Lastpage :
1136
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.
Keywords :
digital forensics; higher order statistics; image enhancement; image forensics; matrix algebra; co-occurrence matrix; contrast enhancement counter-forensics; contrast enhancement detection; counter-forensic attacks; first-order statistics; histogram-based processing; image forensic analysis; image histogram; second-order statistics analysis; Digital images; Histograms; Image forensics; Materials; Oscillators; Statistical analysis; Counter-forensics; forensic analysis; histogram-based processing; second-order statistics; statistical analysis;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2015.2389241
Filename :
7004806
Link To Document :
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