Nonparametric steganalysis of QIM steganography using approximate entropy

Hafiz Malik, K. P. Subbalakshmi, R. Chandramouli

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This paper proposes an active steganalysis method for quantization index modulation (QIM)-based steganography. The proposed nonparametric steganalysis method uses irregularity (or randomness) in the test image to distinguish between the cover image and the stego image. We have shown that plain quantization (quantization without message embedding) induces regularity in the resulting quantized object, whereas message embedding using QIM increases irregularity in the resulting QIM-stego. Approximate entropy, an algorithmic entropy measure, is used to quantify irregularity in the test image. The QIM-stego image is then analyzed to estimate secret message length. To this end, the QIM codebook is estimated from the QIM-stego image using first-order statistics of the image coefficients in the embedding domain. The estimated codebook is then used to estimate secret message. Simulation results show that the proposed scheme can successfully estimate the hidden message from the QIM-stego with very low decoding error probability. For a given cover object the decoding error probability depends on embedding rate and decreases monotonically, approaching zero as the embedding rate approaches one.

Original languageEnglish
Article number6025286
Pages (from-to)418-431
Number of pages14
JournalIEEE Transactions on Information Forensics and Security
Volume7
Issue number2
DOIs
StatePublished - Apr 2012

Keywords

  • Algorithmic entropy
  • approximate entropy
  • complexity
  • dither modulation
  • embedding rate
  • entropy
  • message recovery
  • quantization index modulation
  • steganalysis
  • steganography

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