Article

A new approach to estimating hidden message length in stochastic modulation steganography

Authors:

Junhui He,

Jiwu Huang,

Guoping QiuAuthors Info & Claims

IWDW'05: Proceedings of the 4th international conference on Digital Watermarking

Pages 1 - 14

https://doi.org/10.1007/11551492_1

Published: 15 September 2005 Publication History

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Abstract

Stochastic modulation steganography hides secret message within the cover image by adding a weak noise signal with a specified probabilistic distribution. The advantages of stochastic modulation steganography include high capacity and better security. Current steganalysis methods that are applicable to the detection of hidden message in traditional least significant bit (LSB) or additive noise model based steganography cannot reliably detect the existence of hidden message in stochastic modulation steganography. In this paper, we present a new steganalysis approach which can reliably detect the existence and accurately estimate the length of hidden message in stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of the images before and after stochastic modulation embedding, it is shown that for non-adaptive steganography, the distribution of the stego-image’s pixel difference can be modeled as the convolution of the distribution of the cover image’s pixel difference and that of the quantized stego-noise difference, and that the estimation of the hidden message length in stochastic modulation can be achieved by estimating the variance of the stego-noise. To estimate the variance of the stego-noise, hence determining the existence and the length of hidden message, we first model the distribution of the cover image’s pixel difference as a generalized Gaussian and estimate the parameters of the distribution using grid search and Chi-square goodness of fit test, and then exploit the relationship between the distribution variance of the cover image’s pixel difference and that of the stego-noise difference. We present experimental results to demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography. Our method provides a general theoretical framework and is applicable to other non-adaptive embedding algorithms where the distribution models of the stego-noise are known or can be estimated.

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Setiadi DRustad SAndono PShidik G(2023)Digital image steganography survey and investigation (goal, assessment, method, development, and dataset)Signal Processing10.1016/j.sigpro.2022.108908206:COnline publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2022.108908
Wang ALi ZPeng CShen GFang GZeng BBorriello GPau GGruteser MHong J(2015)InFrame++Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services10.1145/2742647.2742652(181-195)Online publication date: 18-May-2015
https://dl.acm.org/doi/10.1145/2742647.2742652
Wang APeng CZhang OShen GZeng BKatz-Bassett EHeidemann JGodfrey BFeldmann A(2014)InFrameProceedings of the 13th ACM Workshop on Hot Topics in Networks10.1145/2670518.2673867(1-7)Online publication date: 27-Oct-2014
https://dl.acm.org/doi/10.1145/2670518.2673867

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Published In

IWDW'05: Proceedings of the 4th international conference on Digital Watermarking

September 2005

505 pages

ISBN:354028768X

Editors:
Mauro Barni
Dipartimento di Ingegneria dell'Informazione, Università degli Studi di Siena, Italy
,
Ingemar Cox
Dipartimento di Ingegneria dell'Informazione, University College London, Torrington Place, UK
,
Ton Kalker
Dipartimento di Ingegneria dell'Informazione, Hewlett-Packard Laboratories, Palo Alto, CA, UK
,
Hyoung-Joong Kim
Multimedia Security Lab, Korea University, Science Campus, Seoul, CA, Korea

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Springer-Verlag

Berlin, Heidelberg

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Published: 15 September 2005

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Setiadi DRustad SAndono PShidik G(2023)Digital image steganography survey and investigation (goal, assessment, method, development, and dataset)Signal Processing10.1016/j.sigpro.2022.108908206:COnline publication date: 1-May-2023
https://dl.acm.org/doi/10.1016/j.sigpro.2022.108908
Wang ALi ZPeng CShen GFang GZeng BBorriello GPau GGruteser MHong J(2015)InFrame++Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services10.1145/2742647.2742652(181-195)Online publication date: 18-May-2015
https://dl.acm.org/doi/10.1145/2742647.2742652
Wang APeng CZhang OShen GZeng BKatz-Bassett EHeidemann JGodfrey BFeldmann A(2014)InFrameProceedings of the 13th ACM Workshop on Hot Topics in Networks10.1145/2670518.2673867(1-7)Online publication date: 27-Oct-2014
https://dl.acm.org/doi/10.1145/2670518.2673867

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High-performance JPEG steganography using quantization index modulation in DCT domain

On Estimation of Secret Message Length in JSteg-like Steganography

Estimation of the Hidden Message Length in Steganography: A Deep Learning Approach

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