Steganalysis using image quality metrics

Ismail Avcibaş, Nasir Memon, Bülent Sankur

Research output: Contribution to journalArticlepeer-review


We present techniques for steganalysis of images that have been potentially subjected to steganographic algorithms, both within the passive warden and active warden frameworks. Our hypothesis is that steganographic schemes leave statistical evidence that can be exploited for detection with the aid of image quality features and multivariate regression analysis. To this effect image quality metrics have been identified based on the analysis of variance (ANOVA) technique as feature sets to distinguish between cover-images and stego-images. The classifier between cover and stego-images is built using multivariate regression on the selected quality metrics and is trained based on an estimate of the original image. Simulation results with the chosen feature set and well-known watermarking and steganographic techniques indicate that our approach is able with reasonable accuracy to distinguish between cover and stego images.

Original languageEnglish (US)
Pages (from-to)221-229
Number of pages9
JournalIEEE Transactions on Image Processing
Issue number2
StatePublished - Feb 2003


  • Analysis of variance
  • Image quality measures
  • Multivariate regression analysis
  • Steganalysis
  • Steganography
  • Watermarking

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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