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Steganalysis of SS Steganography: Hidden Data Identification and Extraction

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Abstract

We consider the problem of steganalysis of multi-carrier spread-spectrum steganography in which secret data are embedded over a wide band in a spectrum (transform) domain of a digital medium. The objective is first to identify the presence or absence of hidden data in a given image (i.e., passive steganalysis). Unlike conventional feature-based passive steganalysis algorithms, we describe an unsupervised (blind) low-complexity approach based on iterative generalized least-squares principles that may enable rapid high-volume image processing. Extensive experiments on image sets and comparisons with existing passive steganalysis techniques demonstrate most satisfactory classification performance measured in probability of correct detection versus induced false alarm rate. If the existence of hidden data is identified, we then aim to detect the number of carriers (messages) and blindly extract the hidden data without the knowledge of the original host nor the embedding carriers. This task is also known as active/forensic steganalysis. Experimental studies on images show that the developed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers.

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Notes

  1. Active steganalysis is also referred to as forensic steganalysis [11].

  2. Most conventional SS embedding schemes [2, 6, 9, 16, 25, 30, 36] consider single message embedding which is a special case of the multi-message SS embedding.

  3. Additive white Gaussian noise is frequently viewed as a suitable (most entropic) model for general quantization errors, channel transmission disturbances, and/or image processing attacks [5].

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Authors and Affiliations

  1. School of Information and Communication Engineering, Dalian University of Technology, Dalian, 116024, Liaoning, China

    Ming Li

  2. Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, NY, 14228, USA

    Qian Liu

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  1. Ming Li
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  2. Qian Liu
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Correspondence to Ming Li.

Additional information

This work was supported by the Fundamental Research Funds for the Central Universities (Grant No. DUT14RC(3)103). This paper was presented in part at the IEEE Int. Conf. Image Process. (ICIP), Brussels, Belgium, Sept. 2011.

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Li, M., Liu, Q. Steganalysis of SS Steganography: Hidden Data Identification and Extraction. Circuits Syst Signal Process 34, 3305–3324 (2015). https://doi.org/10.1007/s00034-015-0007-7

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