Statistical Detection of LSB Matching Using Hypothesis Testing Theory

  • Rémi Cogranne
  • Cathel Zitzmann
  • Florent Retraint
  • Igor Nikiforov
  • Lionel Fillatre
  • Philippe Cornu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7692)

Abstract

This paper investigates the detection of information hidden by the Least Significant Bit (LSB) matching scheme. In a theoretical context of known image media parameters, two important results are presented. First, the use of hypothesis testing theory allows us to design the Most Powerful (MP) test. Second, a study of the MP test gives us the opportunity to analytically calculate its statistical performance in order to warrant a given probability of false-alarm. In practice when detecting LSB matching, the unknown image parameters have to be estimated. Based on the local estimator used in the Weighted Stego-image (WS) detector, a practical test is presented. A numerical comparison with state-of-the-art detectors shows the good performance of the proposed tests and highlights the relevance of the proposed methodology.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rémi Cogranne
    • 1
  • Cathel Zitzmann
    • 1
  • Florent Retraint
    • 1
  • Igor Nikiforov
    • 1
  • Lionel Fillatre
    • 1
  • Philippe Cornu
    • 1
  1. 1.ICD, LM2SUniversité de Technologie de Troyes, UMR STMR CNRSTroyes cedexFrance

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