Self-adaptive cost sensitive feature learning method for unbalanced JPEG image steganography detection

A steganographic detection and cost-sensitive technology, applied in image watermarking, image data processing, image data processing, etc., can solve problems such as reliability degradation

Active Publication Date: 2020-07-14
WUHAN UNIV
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Problems solved by technology

[0014] The present invention aims at the problem that the reliability of the detection results of the existing steganalysis method decreases i

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  • Self-adaptive cost sensitive feature learning method for unbalanced JPEG image steganography detection
  • Self-adaptive cost sensitive feature learning method for unbalanced JPEG image steganography detection
  • Self-adaptive cost sensitive feature learning method for unbalanced JPEG image steganography detection

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Embodiment Construction

[0059] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0060] When misclassification occurs, the classifier based on the cost-sensitive feature learning method is modified to be adaptively cost-sensitive by assigning different weights to each sample. Representative features are learned according to the classifier with the largest F-measure by optimizing a series of adaptive cost-sensitive feature selection subproblems. Therefore, we consider the difference of samples in the same class, and the selected features can adequately represent the cover class and the stego class.

[0061] The main structure of the proposed scheme is as follows figure 1 shown. It includes the following three main stages: (1) preprocessing of imbalanced samples; (2) adaptive total cost generation; (3) F-measure optimization and feature extraction.

[0062] Specifically, the unbalanced sample preprocessin...

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Abstract

The invention discloses a self-adaptive cost sensitive feature learning method for unbalanced steganography detection. According to the method, for an unbalanced JPEG image steganography detection environment, in order to solve problem that the detection effectiveness of a traditional steganalysis method is greatly reduced under the condition of unbalanced data distribution, an unbalanced data set-oriented steganography detection scheme is realized mainly from the following three aspects: firstly, an unbalanced sample preprocessing method is provided, the optimal k value of a dynamic k nearestneighbor algorithm (DkNN) of each sample is determined, and the intra-class cost is obtained according to the proportion of classes; secondly, an adaptive cost sensitive classifier is generated basedon the intra-class and inter-class cost of each training sample; and finally, the feature corresponding to the maximum F metric is obtained through the F metric maximization and regularization logistic regression adaptive cost-sensitive classifier and the effective feature acquisition.

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 unbalanced steganographic detection for judging whether a JPEG image has been embedded with secret information when the number of samples of different categories in a training data set is greatly different. Background technique [0002] Steganography is a covert communication technique that embeds secret data into an image by modifying the image's pixels or frequency coefficients in an imperceptible manner [1] . Due to the wide application of the JPEG format, many steganographic algorithms have been designed for the JPEG domain. In contrast, image steganalysis focuses on the presence or absence of secret information in digital images [2] . Modern steganalysis algorithms are emerging, trying to identify some specific statistical features that can effectively distinguish cover and stego images. [0003] Although th...

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Application Information

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IPC IPC(8): G06T1/00G06K9/62
CPCG06T1/0021G06T2201/005G06F18/2411G06F18/214
Inventor 王丽娜嘉炬翟黎明任魏翔
Owner WUHAN UNIV
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