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Steganographic Algorithm Unknown Information Hiding Detection Method

A detection method and information hiding technology, applied in computing, computer parts, instruments, etc., can solve the problems of reduced detection accuracy, ignorance of dense image embedding algorithms, etc.

Active Publication Date: 2020-10-16
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In practical applications, when detecting a batch of normal images and mixed images containing secret information images, we do not know the embedding algorithm used by the secret image, and the classifier is trained according to the existing steganography algorithm, and the detection accuracy will be greatly improved. reduce, so it is impossible to train a classifier to classify with traditional methods

Method used

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  • Steganographic Algorithm Unknown Information Hiding Detection Method

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Embodiment 1

[0033] Firstly, the feature extraction method and learning algorithm used in the process of the method of the present invention are introduced.

[0034] DCTR (Discrete Cosine Transform Residual): By decompressing the JPEG image into the airspace, using the characteristics of the statistical histogram, the 8000-dimensional DCTR feature is obtained.

[0035] GFR (Gabor Filter JPEG Rich Model): Decompress JPEG images by using 2D Gabor filters with different scales and directions, and extract 17,000-dimensional features from the filtered images.

[0036] FLD (Fisher Linear Discriminant): The basic idea is to project the two types of sample sets into one direction as much as possible, so that the classes are separated as much as possible. divergence as large as possible.

[0037] K-means: It is a typical distance-based clustering algorithm, which uses distance as a similar evaluation index, that is, the closer the distance between two features is, the greater the similarity is, an...

Embodiment 2

[0048] Embodiment 2: This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0049] A batch of mixed images in the step 1) includes 800 normal images and 200 dense images as a test set. The steganographic algorithms used are J_UNIWORD and UERD. The steganographic algorithms used for the encrypted image are not known during the detection, and the image features are DCTR and GFR. see figure 2 is the distribution of the image dataset, Represents the features of normal images, ●Represents the features of secret images, normal images are used as majority class samples, and secret images are used as minority class samples, the closest to each minority class sample point is the majority class sample point, and this distribution will be used later Features add new data points for minority class samples.

[0050] Described step 2) utilizes FLD algorithm and K-means to establish algorithm model, obtains optimal projection vector

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Abstract

The present invention relates to an information hiding detection method whose steganography algorithm is unknown, and the specific operation steps are as follows: 1) judging which images in a batch of images contain secret information; 2) establishing an algorithm model by using the FLD algorithm and K-means clustering algorithm; 3 ) Estimate the optimal projection vector and detect this batch of images; 4) Use the integrated classifier to cast the pre-classified results; 5) Use the unbalanced algorithm to match the balance; 6) Use the newly generated data set to retrain the integrated classifier; 7 ) and then use the integrated classifier to cast the final classification result. The present invention can effectively solve the practical problem of unlabeled and unbalanced data sets.

Description

technical field [0001] The invention relates to an information hiding detection method with unknown steganography algorithm. Background technique [0002] Information hiding is to hide secret information into normal carriers and realize secret communication. Image steganography is the use of images to hide secret information and achieve the purpose of covert communication. Steganalysis is to judge whether the carrier contains secret information, and it has irreplaceable importance in many fields related to information security, such as politics, military affairs, and the Internet. In practical applications, when detecting a batch of normal images and mixed images containing secret information images, the embedding algorithm used by the secret image is unknown, and the classifier is trained according to the existing steganography algorithm, and the detection accuracy will be greatly improved. Therefore, it is impossible to train a classifier for classification with traditio...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06T1/00
CPCG06T1/0021G06F18/21322G06F18/2411
Inventor 冯国瑞傅佳孙艳曾喜梅
Owner SHANGHAI UNIV
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