• 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