Nonparametric Steganalysis of QIM Data Hiding using Approximate Entropy |
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Hafiz Malik, K. P. Subbalakshmi and R. Chandramouli Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey, USA
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AbstractThis 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). |