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JPEG image mismatch steganography analysis method based on heterogeneous characteristic subspace migration

A feature subspace, steganalysis technology, applied in image communication, digital video signal modification, electrical components, etc., can solve the problem of steganalysis method detection rate decline and so on

Active Publication Date: 2019-02-15
WUHAN UNIV
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Problems solved by technology

[0011] The present invention aims at the problem that the detection rate of the existing steganalysis method decreases in a mismatch environment, and realizes a mismatch steganalysis method capable of transferring effective information from a mismatch data set

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  • JPEG image mismatch steganography analysis method based on heterogeneous characteristic subspace migration
  • JPEG image mismatch steganography analysis method based on heterogeneous characteristic subspace migration
  • JPEG image mismatch steganography analysis method based on heterogeneous characteristic subspace migration

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Embodiment Construction

[0079] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0080] Some variables involved in the present invention are defined in Table 1.

[0081] Some symbols and meanings used in the present invention of table 1

[0082]

[0083] Such as figure 2 Shown, concrete flow process of the present invention is:

[0084] Step 1, select the mismatched image set, including training data set (source domain data set) and test data set (target domain data set);

[0085] Step 2, for the mismatched image set, use low-rank constraints to perform local information transfer on domain-independent features;

[0086] The purpose of domain-independent feature migration is to migrate the data of the source domain and the target domain into the feature subspace by finding a transformation matrix, and ensure that the distributions of the source domain and the target domain are approximately equal. S...

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Abstract

The invention relates to a JPEG image mismatch steganography analysis method based on heterogeneous characteristic subspace migration. The method provided by the invention takes characteristics of different fields as a combination of domain-independent and domain-related characteristic subspaces, and the method comprises the following steps: firstly providing a low-rank constrained domain-independent characteristic migration method, and realizing local information migration by utilizing local data characteristics between different fields; secondly, based on sparse representation of modeling domain-related characteristics, measuring influence produced by field change on the modeling domain-related characteristics; and finally, by virtue of the steps, constructing an objective function, andsolving by virtue of an imprecise augmented Lagrange multiplier method. Unique global information of the domain-related characteristics is considered while local information migration is realized in adomain-independent characteristic subspace, so that characteristic differentiation degree between a cover image and a stego image can be improved, detection effect of mismatch steganography analysiscan be beneficially improved, and great significance is produced to the mismatch steganography analysis.

Description

technical field [0001] The invention relates to the technical field of multimedia security and digital media processing, in particular to the technical field of mismatch steganalysis for judging whether a JPEG image has been embedded with secret information under the condition that the distribution of the training set and the test set are inconsistent. Background technique [0002] Steganography is the process of concealing secret information in digital media in an imperceptible form to achieve covert communication. Since images in JPEG format are widely used, the steganography of JPEG images develops rapidly. Steganalysis is a reverse detection technology that is opposed to steganography. Its purpose is to judge whether there is hidden information in the carrier according to the statistical characteristics of the carrier. [0003] At present, most steganalysis methods use machine learning tools to obtain a detection model by training the extracted feature data, and then us...

Claims

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Application Information

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IPC IPC(8): H04N19/467H04N1/32
CPCH04N1/32272H04N19/467
Inventor 王丽娜嘉炬任魏翔翟黎明徐一波
Owner WUHAN UNIV
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