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Information hiding detection method under unknown steganographic algorithm situation

A detection method and information hiding technology, which is applied in the field of information hiding detection where the steganography algorithm is unknown, can solve the problems of not knowing the embedding algorithm of the encrypted image and reducing the detection accuracy

Active Publication Date: 2017-10-20
SHANGHAI UNIV
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  • Application Information

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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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  • Information hiding detection method under unknown steganographic algorithm situation
  • Information hiding detection method under unknown steganographic algorithm situation
  • Information hiding detection method under unknown steganographic algorithm situation

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Experimental program
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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 nearest to each minority class sample point is the majority class sample point, and this distribution will be used later Features add new data points to 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 invention relates to an information hiding detection method under an unknown steganographic algorithm situation. The method comprises the following specific operation steps that: 1) judging which images in one bath of images contain secret information; 2) utilizing an FLD (Fisher Linear Discriminant) algorithm and a K-means clustering algorithm to establish an algorithm model; 3) estimating an optimal projection vector, and detecting the batch of images; 4) utilizing an ensemble classifier to output a pre-classification result; 5) utilizing an unbalanced algorithm to carry out balance coordination; 6) utilizing a new dataset to train the ensemble classifier again; and 7) reusing the ensemble classifier to output a final classification result. By use of the method, the practical problem of situations of no labels and unbalanced datasets can be effectively solved.

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 Applications(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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