Nonparametric Steganalysis of QIM Data Hiding using Approximate Entropy

 

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

Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, USA

 

Abstract

This paper proposes a nonparametric steganalysis method for quantization index modulation (QIM) based steganography. The proposed 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-image; whereas message embedding using QIM increases irregularity in the resulting QIM-stego image. Approximate entropy, an algorithmic entropy measure, is used to quantify irregularity in the test-image. Simulation results presented in this paper show that the proposed steganalysis technique can distinguish between the cover- and the stego-image with low false rates (i.e. Pfp<0.1 and Pfn<0.07).

 Download   

full version in PDF 

Presentation Slides

 Back to Malik's homepage