Steganalytic features for JPEG compression-based perturbed quantization

Gul G., Dirik A. E., Avcibas I.

IEEE SIGNAL PROCESSING LETTERS, vol.14, no.3, pp.205-208, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 3
  • Publication Date: 2007
  • Doi Number: 10.1109/lsp.2006.884010
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.205-208
  • Bursa Uludag University Affiliated: No


Perturbed quantization (PQ) data hiding is almost undetectable with the current steganalysis methods. We briefly describe PQ and propose singular value decomposition (SVD)-based features for the steganalysis of JPEG-based PQ data hiding in images. We show that JPEG-based PQ data hiding distorts linear dependencies of rows/columns of pixel values, and proposed features can be exploited within a simple classifier for the steganalysis of PQ. The proposed steganalyzer detects PQ embedding on relatively smooth stego images with 70% detection accuracy on average for different embedding rates.