CN115314601A

CN115314601A - Lossy format data steganography method and device

Info

Publication number: CN115314601A
Application number: CN202211245471.XA
Authority: CN
Inventors: 郝伟; 沈传宝
Original assignee: Anhui Huayun'an Technology Co ltd
Current assignee: Anhui Huayun'an Technology Co ltd
Priority date: 2022-10-12
Filing date: 2022-10-12
Publication date: 2022-11-08
Anticipated expiration: 2042-10-12
Also published as: CN115314601B

Abstract

The embodiment of the invention provides a method and a device for steganography of data in a lossy format. The method comprises the following steps: the method comprises the steps of carrying out data quantization and steganography on frequency domain information of an original image to obtain a steganography quantization matrix, fitting the steganography quantization matrix to obtain a fitting matrix, carrying out data quantization on the frequency domain information of the fitting matrix, comparing the frequency domain information with the steganography quantization matrix to obtain a secret key matrix, adding the secret key matrix to the steganography quantization matrix to obtain an encryption steganography matrix, and encoding the encryption steganography matrix to obtain a steganography image. In this way, the data steganography of the lossy format can be completed, the data loss is reduced, and the accuracy of extracting the steganographic data is ensured.

Description

Lossy format data steganography method and device

Technical Field

The invention relates to the field of information security, in particular to the technical field of lossy format data steganography.

Background

The image information steganography technology of the lossless picture format is easy to be identified by a third party, and the information leakage risk is high. In the process of data steganography in a lossy format, on one hand, the difficulty of the steganography process in a frequency domain is high, and on the other hand, pixel points are lost before and after image compression, so that the original information in the frequency domain cannot be decrypted correctly, the acquisition of steganography data is influenced, and the reading accuracy of the steganography data is reduced.

Disclosure of Invention

The invention provides a method and a device for steganography of lossy format data.

According to a first aspect of the invention, a lossy format data steganography method is provided. The method comprises the following steps:

acquiring data to be steganographically and an original image; the original image is agreed by a data steganography party and a data extraction party in advance;

determining frequency domain information of the original image, and performing data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

adding the data to be steganographically into the original quantization matrix according to a preset rule to obtain a steganographically quantization matrix;

fitting the steganographic quantization matrix to obtain a fitting matrix;

after the frequency domain information of the fitting matrix is subjected to data quantization, comparing the frequency domain information with the steganography quantization matrix to obtain a key matrix;

adding the secret key matrix into the steganography quantization matrix to obtain an encryption steganography matrix;

and coding the encrypted steganography matrix to obtain a steganography image.

As to the above-mentioned aspect and any possible implementation manner, further providing an implementation manner, where adding the data to be steganographically written to the original quantization matrix according to a preset rule to obtain a steganographically written quantization matrix includes: the data steganography side and the data extraction side predetermine a steganography mode of the data to be steganography, and the data to be steganography is added into the original quantization matrix; or

And the data steganography side determines a steganography mode of the data to be steganographically written, adds the data to be steganographically written into the original quantization matrix, and adds the steganography mode of the data to be steganographically written into the steganography image.

The above-described aspect and any possible implementation further provide an implementation, where the steganographic manner includes:

adding position information of elements of data to be steganographically written into the original quantization matrix;

the data to be hidden is added to the sequence information of the elements of the data to be hidden.

As for the above-mentioned aspect and any possible implementation manner, there is further provided an implementation manner that adds the data to be steganographically written to the original quantization matrix according to a preset rule to obtain a steganographically written quantization matrix, including:

and converting the data to be steganographically into binary data.

As with the above-described aspects and any possible implementations, further providing an implementation that fitting the steganographic quantization matrix to obtain a fitting matrix includes:

and the steganographic quantization matrix obtained after adding the steganographic data is in a YUV format, and the fitting matrix obtained after fitting is in an RGB format.

According to a second aspect of the present invention, there is provided a lossy format data extraction method applied to a data extractor. The method comprises the following steps:

acquiring a steganographic image, and decoding the steganographic image to determine a steganographic quantization matrix of the steganographic image;

obtaining frequency domain information of an original image, and carrying out data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

comparing the original quantization matrix with a steganographic quantization matrix of a steganographic image to obtain difference data;

and obtaining steganographic data based on the difference data and a preset rule.

According to a third aspect of the present invention, there is provided a lossy formatted data steganography apparatus. The device includes:

the information acquisition module is used for acquiring data to be concealed and an original image; the original image is agreed by a data steganography party and a data extraction party in advance;

the data quantization module is used for determining the frequency domain information of the original image and performing data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

the steganographic data adding module is used for adding the to-be-steganographic data into the original quantization matrix according to a preset rule to obtain a steganographic quantization matrix;

the fitting module is used for fitting the steganographic quantization matrix to obtain a fitting matrix;

the secret key obtaining module is used for comparing the frequency domain information of the fitting matrix with the steganography quantization matrix to obtain a secret key matrix after the data quantization is carried out on the frequency domain information of the fitting matrix;

the secret key adding module is used for adding the secret key matrix into the steganography quantization matrix to obtain an encryption steganography matrix;

and the coding module is used for coding the encrypted steganographic matrix to obtain a steganographic image.

According to a fourth aspect of the present invention, there is provided a lossy formatted data steganography apparatus. The device comprises:

the steganographic image quantization module is used for acquiring a steganographic image, decoding the steganographic image and determining a steganographic quantization matrix of the steganographic image;

the original image quantization module is used for obtaining frequency domain information of an original image and carrying out data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

the comparison module is used for comparing the original quantization matrix with a steganographic quantization matrix of a steganographic image to obtain difference data;

and the extraction module is used for obtaining the steganographic data based on the difference data and a preset rule.

The method disclosed by the embodiment of the invention can reduce the data error before and after the lossy picture format is compressed, and improve the accuracy and the safety of the steganography of the lossy format data.

It should be understood that the statements made in this summary are not intended to limit the key or critical features of the embodiments of the present invention, or to limit the scope of the invention. Other features of the present invention will become apparent from the following description.

Drawings

The above and other features, advantages and aspects of various embodiments of the present invention will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention:

FIG. 1 illustrates a flow diagram of a lossy format data steganography method in which embodiments of the present invention can be implemented;

FIG. 2 illustrates a schematic diagram of a lossy format data steganography method in which embodiments of the present invention can be implemented;

FIG. 3 illustrates a flow diagram of one steganographic approach in which embodiments of the present invention can be implemented;

FIG. 4 illustrates a flow diagram of a lossy format data extraction method in which embodiments of the present invention can be implemented;

FIG. 5 illustrates a schematic diagram of a lossy formatted data steganographic apparatus in which embodiments of the present invention can be implemented;

FIG. 6 shows a schematic diagram of a lossy format data extraction apparatus in which an embodiment of the invention can be implemented;

FIG. 7 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without inventive efforts based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.

In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

According to the method, loss values before and after the lossy format data is steganographically are researched, a reasonable fitting method is adopted, the loss values are added into the steganographically quantized matrix in advance, decoding information obtained after the steganographically quantized matrix is coded and decoded is compared with original information to obtain steganographically data, the influence of color system noise and quantization noise on the steganographically data is reduced, and the accuracy of obtaining the steganographically data in the lossy data transmission process is improved.

Fig. 1 and 2 show a flow chart and a schematic diagram, respectively, of a lossy formatted data steganography method in which embodiments of the present invention can be implemented, as shown in fig. 1, the method 100 comprising:

step 110: acquiring data to be steganographically and an original image; the original image is agreed by a data steganography party and a data extraction party in advance;

it should be noted that, in the embodiment of the present invention, the data to be steganographically written may include, but is not limited to, data that a data sender wants to encrypt, including, but not limited to, confidential data of a unit, business data of an enterprise, data of an individual, privacy, and the like. Certainly, the data to be steganographically written may also be digital watermarks and the like to protect image copyrights, and those skilled in the art may set the data according to actual requirements, which is not described herein again.

The data steganographer and the data extractor need to define an original image in advance, that is, the data steganographer and the data extractor need to set in advance which image the data to be steganographed is to be added to, and acquire the image in advance.

Step 120: determining frequency domain information of the original image, and performing data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

in the embodiment of the invention, a JPEG image is taken as an example, and frequency domain information of the image is obtained according to the following steps:

1) Carrying out image segmentation on an original image to obtain an image block;

the original image needs to be first divided into a plurality of small blocks, wherein the size of the plurality of small blocks can be set by those skilled in the art. These small blocks are all handled separately in embodiments of the invention. That is, to separately perform steganography of data to be steganographically, in the embodiment of the present invention, the image may be divided into a plurality of small blocks with a size of 8 × 8, but not limited to this.

2) Carrying out color space transformation on image blocks obtained by image segmentation;

"color space" refers to a mathematical model for expressing color, such as the common "RGB" model, which decomposes the color into three components of red, green and blue, so that a picture can be decomposed into three gray-scale images, and each 8 × 8 image can be expressed as three 8 × 8 matrixes in mathematical expression, wherein the range of the numerical values in the matrixes is generally between [0, 255 ]. Different color models have different application scenarios, for example, the RGB model is suitable for self-luminous patterns such as a display, and in the JPEG compression algorithm, the pattern needs to be converted into a YUV color system model, where Y represents Luminance (Luminance) and U and V represent "color difference" of chromaticity, respectively. The method for converting the original image into the YUV can refer to the prior art, and is not described herein any more, and after color conversion, two-dimensional matrixes corresponding to a Y component, a U component and a V component in the YUV model corresponding to the original image can be obtained respectively.

3) Fourier transform is carried out on the two-dimensional matrix obtained by color space transform to obtain frequency domain information of the image block;

the method comprises the steps of converting space domain data of an original image into frequency domain data based on an obtained two-dimensional matrix corresponding to the original image, wherein Discrete Cosine Transform (DCT) belongs to another form of Fourier Transform, and converting space domain information of the original image into frequency domain information through the DCT.

In some embodiments of the present invention, the order of step 1) and step 2) may be changed, that is, the image is first converted from RGB color system to YUV color system, and then the read-in image is divided into 8 × 8 blocks.

In some embodiments of the present invention, a block is taken within the original image, divided into a 64-grid array of 8 × 8 pixels. By sampling the luminance (or chrominance of interest) values from pixel to pixel and matrix-forming the array of luminance values for the pixels). Each spatial sample value may then be converted into a frequency domain value, referred to herein as a DCT coefficient, using a Discrete Cosine Transform (DCT), illustratively given by the formula:

；

for the 64-point array described above, 64 DCT coefficients are available for conversion to the rectangular array table of Table 1. The method changes an array consisting of 64 point image sampling values into a 64 point array consisting of a direct current average value and 63 cosine wave amplitude values with different frequencies, and the array is called as a DCT coefficient array. After the transformation, the data of the spatial coordinates are converted into data of frequency coordinates, i.e., DCT frequency coefficients. After sampling and quantizing the values of the pixels of the original 8 × 8 block, the values are converted into the spectral coefficients of the frequency domain image signal, that is, the spectral coefficients can be expressed by 64 frequency coefficients, which are called 64 "orthogonal base signals", and each base signal corresponds to one of 64 independent two-dimensional spatial frequencies. These spatial frequencies are made up of the "spectrum" of the input signal. Of the 64 resulting transform coefficients, the first term represents the dc component, i.e. the average of the 64 spatial image sample values, and the remaining 63 coefficients represent the amplitude of the respective base signal.

TABLE 1 frequency domain local table corresponding to Y table after Discrete Cosine Transform (DCT) of the embodiments of the present invention

Observing the data in table 1, the rule can be found, the value of the upper left corner of the matrix is larger, and the value of the lower right corner is smaller and approaches to zero. Thus, the DCT coefficients for each base signal may be tabulated in zigzag scan order. The DCT coefficients are arranged into a data series according to the rule, and the coding sequence of the DCT coefficients is formed. After the above processing, the two-dimensional data amount is converted into a one-dimensional data amount, the first term of the array is the average brightness value of the block, and the distribution and the size of the coefficients of the following terms can reflect the intensity of brightness fluctuation. If the coefficient is larger, the brightness fluctuation is larger, and the image contour of the area is finer; if the numerical value is smaller, the brightness change in the area is more smooth; if the value is zero, the high frequency component value in the array is zero, and the brightness level is unchanged. In the actual data processing, the values of the coefficients arranged in the following are basically zero or tend to be zero. The detail condition of the image in the block, namely the image definition condition, can be reflected by 63 coefficient sets and the change condition.

In the matrix list of table 1, the values at the upper left corner are larger, and they represent the dc component and the low frequency component of the image information, and are the main part of the image information and the main part of the information in the block; the lower right-hand corners have smaller values, which represent high frequency components of the image information, and the amplitudes of the high frequency components are originally smaller and mainly reflect the detailed parts of the image. Human eyes have higher relative sensitivity to the brightness information of the image and are not sensitive enough to the color information of the image; in addition, the human eye has a high visual sensitivity to low-frequency components of image information. The data series formed after the zigzag character scanning just forms a good corresponding relation with the sensitivity of human eyes to image information. The image data may be compressed according to the above-described laws of visual physiology.

After DCT transformation (here, transformation refers to forward transformation, that is, from spatial domain to frequency domain, and if the inverse is inverse DCT transformation), then data quantization is performed on the image, and some useless information in the image is extracted, so as to represent the maximum information amount with the minimum space. Human eyes are not sensitive to high-frequency components, so that the high-frequency components are removed, the storage space of the image can be reduced, and meanwhile, the human eyes cannot lose information.

In some embodiments of the invention, the process of data quantization comprises: the values in the matrix are divided by a "value" in turn and then rounded, but the matrix divided by the value cannot be chosen arbitrarily. The 'values' to be divided are collected into a table, namely a quantization table, the quantization table given by the JPEG official party is adopted, the quantization table comprises two quantization tables, one quantization table is used for quantization of a Y table, the other quantization table is used for quantization of a 'U, V' table, the quantization table of the Y table is shown in a table 2, and a matrix obtained after data quantization processing is shown in a table 3.

TABLE 2 quantization tables corresponding to Y tables of embodiments of the present invention

Table 3. Local data table after data quantization of frequency domain corresponding to Y table after discrete cosine transform in the embodiment of the present invention

In the embodiment of the present invention, the frequency domain information is subjected to data quantization for the purpose of preparing for steganography, and the quantized data information has at least two benefits:

1) The rounded numbers have no decimal, so the operation is more convenient;

2) Eliminating decimal and large number is convenient for eliminating useless information.

It should be noted that, the JPEG compression technique may remove the unimportant part of the original image, so that the image may be stored in a smaller volume, wherein in the lossy compression process, the data quantization process may filter out the detail information in the frequency domain information of the original image, thereby achieving the effect of reducing the volume of the image, and the data quantization is an irreversible process, and the lost data cannot be found back any more during the data quantization. Those skilled in the art can also set the quantization coefficient matrix for data quantization according to actual requirements, and details are not repeated here.

If a picture is subjected to multiple JPEG compression, the loss of pixel point values of the image is not only due to color system noise, but in fact, the noise mainly comes from two parts, color system noise and quantization noise. Theoretically, only a quantization table adopted by JPEG compression is given, a mathematical mode in a quantization process can be known, and specific quantization noise can be further deduced. Therefore, when the hidden information of the picture is read in, the noise is compensated, so that the hidden information can still be decrypted after the picture is compressed by JPEG for many times.

The quantization table is not necessarily a standard table, and can be formulated according to the requirements of users to realize specific functions, and the data steganography party and the data extraction party can agree with a quantization rule or the quantization table in advance. Therefore, a third party except the data steganographer and the data extractor can hardly obtain the quantization table, so that the compression rule can not be known, the steganographer can not be decoded and obtained, and the data transmission safety is improved.

Step 130: adding the data to be steganographically into the original quantization matrix according to a preset rule to obtain a steganographically quantization matrix;

in order to clarify the adding mode of the data to be steganographically written, so that a data steganographically writer and a data extracting party can quickly and accurately read out information to be steganographically written, in some embodiments of the invention, the data steganographically writer and the data extracting party predetermine the steganographically mode of the data to be steganographically written, and add the data to be steganographically written to the original quantization matrix; or the data steganography side determines a steganography mode of the data to be steganographically, adds the data to be steganographically to the original quantization matrix, and adds the steganography mode of the data to be steganographically to the steganographically image.

In order to avoid the situation that the original image is greatly interfered after the data to be steganographically written is added, and the steganographically written image is greatly changed, when the data to be steganographically written is added into the original quantization matrix, preprocessing is firstly needed to be carried out on the data to be steganographically written, the data to be steganographically written is converted into binary data, and then the binary data is added into the original quantization matrix.

Because information is lost in the data quantization process in the lossy compression process, the invention firstly carries out data quantization on the frequency domain information of the original image and converts the frequency domain information into an original quantization matrix, and then adds data to be steganographically written. Some embodiments of the invention include any one of the following ways of adding data to be steganographically written to an original quantization matrix according to a preset rule to obtain a steganographically quantized matrix:

1) The data steganography side and the data extraction side predetermine a steganography mode of data to be steganographically written, and the data to be steganographically written is added into an original quantization matrix;

2) The data steganography method comprises the steps that a data steganography party determines a steganography mode of data to be steganographically written and adds the data to be steganographically written into an original quantization matrix;

as described above, the data steganography side and the data extraction side may determine the steganography method of the data to be steganography in advance, or may determine the steganography method of the data to be steganography when performing data steganography, and of course, since the original image is divided into a plurality of image blocks of 8 × 8 or other sizes, for example, a part of the sub-blocks is selected first, the steganography method of the data to be steganography in these sub-blocks is defined in advance, and the steganography method of the data in other sub-blocks is determined when the data steganography side steganography data.

Some embodiments of the present invention, after determining when to determine the steganographic mode, need to further determine how to add the steganographic data to the original quantization matrix. Specifically, in the embodiment of the present invention, an individual steganography method may be set for any sub-block of the original image, and the steganography method for adding the data to be steganographed into the original quantization matrix includes:

1) Adding position information of elements of data to be steganographically written into an original quantization matrix;

in the above embodiment, the original image is converted into a plurality of 8 × 8 or other image blocks, so when performing data steganography, the data steganography may be performed by selecting a part of the image blocks, specifically, but not limited to, without causing a large change to the original image, for example, a sub-block with a large element number in the original quantization matrix may be selected for steganography, and specific persons skilled in the art may set the sub-block according to actual needs, which is not described herein again.

Since any sub-block of the original image corresponds to the three quantization matrices of the luminance data Y and the color difference data U and V, after the sub-block which needs to steganographically write data is selected, data steganographically write needs to be performed on one or more of the three quantization matrices.

As another alternative, it may be directly determined to perform steganography on one or more of the three quantization matrices of luminance data Y, color difference data U, and V of each sub-block, and a specific steganography method may be set by a person skilled in the art according to actual needs, which is not limited herein.

After determining to perform data steganography on any original quantization matrix, specific elements in the original quantization matrix need to be selected for data steganography, including but not limited to selecting all or part of the elements. As an optional implementation manner, since most of the non-0 values in the quantization matrix exist in the upper left corner of the matrix and most of the 0 values exist in the lower right corner of the matrix, in order to avoid changing the original image to a greater extent, in the embodiment of the present invention, all or a part of the elements in the upper left corner of the original quantization matrix may be selected to perform data steganography, and similarly, a person skilled in the art may set the values according to actual requirements, which is not described herein again.

2) Adding the data to be steganographically to the sequence information of the elements of the data to be steganographically.

As an optional implementation, a manner of adding the data to be steganographically to the original quantization matrix is given as shown in fig. 3, where a first numerical value of the data to be steganographically is added to elements in a first row and a first column of the original quantization matrix, a second numerical value of the data to be steganographically is added to elements in a first row and a second column of the original quantization matrix, and a third numerical value of the data to be steganographically is added to elements in a first column and a second row of the original quantization matrix until the data to be steganographically preset is completely added to the original quantization matrix, where a specific implementation is shown in fig. 3 and is not described herein again.

Similarly, in the specific implementation process, a person skilled in the art may determine, according to actual requirements, order information of the elements to be steganographically added to the data to be steganographically added.

It should be noted that, after determining the sub-block that needs to be steganographically written, the embodiment of the present invention needs to set order information of the sub-block that needs to be steganographically written, that is, in which sub-block the first part of data of the data to be steganographically written is steganographically written, in which sub-block the second part of data of the data to be steganographically written is steganographically written, and so on.

It should be noted that, if the data steganography party determines the steganography method of the data to be steganographically written when performing data steganography, the steganography method of the data to be steganographically written needs to be added to the steganography image.

Taking a Y table as an example, for a Y table representing brightness, high-frequency information of the Y table is not sensitive to a human eye to transform, so that steganography in some embodiments of the present invention is only performed on the Y table and high-frequency components of the Y table, and the steganography process performs a change on a numerical value, so that the changed numerical value can be used to store steganographic information, and for a specific high-frequency component, which is a specific numerical value, least Significant Bits (LSBs) of the numerical value are changed to store bits of "0,1", so that after converting steganographic information into a binary stream, the steganographic information can be steganographically written in the least significant bits of the frequency coefficients, and the change of the least significant bits is not enough for the human eye to distinguish changed information.

In some embodiments, the program selects the insertion mode to be sequential insertion, that is, the lowest bits of the numbers are extracted and combined together again to obtain the information to be implied.

Step 140: fitting the steganographic quantization matrix to obtain a fitting matrix;

since the image is divided according to 8 × 8 during the preprocessing, the fourier transform of the image is based on 8 × 8 as a basic unit, and after a series of operations, the image generates color noise during the inverse decoding process, which is a main reason for the loss of values.

The error of the color system is caused by at least the following two aspects:

1) The RGB color system is an integer value between 0-255;

2) The JPEG sampling mode is 4:1:1.

after the above data quantization processing, it should be noted that:

1) Natural images tend to be continuous in pixel value;

2) The FDCT (inverse DCT) -transformed and quantized image tends to be continuous in pixel point values. This is because the image has a large number of 0 after data quantization, as shown in table 3, these 0 are also 0 after inverse quantization, that is, some high frequency coefficients are permanently lost, and the loss of these high frequency coefficients causes the pixel point values of the image to tend to be continuous;

3) Since JPEG is a lossy compression, the complete compression process of JPEG needs to be designed and simulated first. The prediction model is also based on a program-simulated JPEG compression procedure, since the aim is to fit the JPEG compression procedure. Due to the fact that JPEG rules used by different systems are slightly different on different platforms and the JPEG compression process is continuously updated, the JPEG complete compression process needs to be fitted.

Since the values of the pixel points tend to be continuous after the image is quantized in the foregoing, in some embodiments of the present invention, the original image is in an RGB format, the original quantization matrix and the steganographic quantization matrix are in a YUV format, and the steganographic quantization matrix in the YUV format is fitted to obtain a fitting matrix in the RGB format.

In some more specific embodiments of the present invention, the value of the upper left corner in the steganographic quantization matrix is taken as the value of each data point of the matrix, that is, the fitting matrix.

Step 150: after the frequency domain information of the fitting matrix is subjected to data quantization, comparing the frequency domain information with the steganographic quantization matrix to obtain a key matrix;

in some embodiments of the present invention, the method for obtaining the frequency domain information of the fitting matrix and the data quantization method are the same as those in step 120, and are not described herein again.

In some embodiments of the present invention, the original image is an RGB format image, an original quantization matrix in a YUV format is obtained after color conversion, blocking and DCT coding, an steganography quantization matrix obtained after adding steganography data is a YUV format, a fitting matrix obtained after fitting is an RGB format, and a fitting quantization matrix obtained after the fitting matrix is DCT converted (obtaining frequency domain information and data quantization) is a YUV format, so that data to be steganography data can be obtained by comparing the fitting quantization matrix with the steganography quantization matrix in the YUV format.

In some embodiments of the invention, the comparing comprises:

1) Subtracting data at a position corresponding to the steganography quantization matrix from a matrix obtained after the frequency domain data quantization of the fitting matrix to obtain a key matrix;

2) And subtracting the data of the matrix corresponding position after the frequency domain data of the fitting matrix is quantized from the steganography quantization matrix to obtain a key matrix.

Step 160: adding the secret key matrix into the steganography quantization matrix to obtain an encryption steganography matrix;

in some embodiments of the invention, the adding comprises:

1) If the matrix obtained by quantizing the frequency domain data of the fitting matrix in the step 150 subtracts the data at the position corresponding to the steganographic quantization matrix to obtain a key matrix, the step 160 subtracts the key matrix from the steganographic quantization matrix to obtain an encrypted steganographic matrix;

2) If the data of the matrix corresponding to the quantized frequency domain data of the fitting matrix is subtracted from the steganographic quantization matrix in step 150 to obtain a key matrix, step 160 adds the steganographic quantization matrix to the key matrix to obtain an encrypted steganographic matrix.

The key matrix has at least two functions:

1) The data loss in the decoding process is supplemented as a secret key, so that correct information can be decrypted by the steganographic image, and information can not be decrypted by the image which is not encrypted under the program condition;

2) The key matrix is essentially the difference value between the decoding matrix of the steganographic image and the original quantization matrix, and the values of the key matrix are difficult to predict and crack because the quantization rule and the compression rule are different.

It can be understood that the key matrix is used to store "loss of precision", and its validity depends on whether the fitting matrix of the prediction is accurate enough, whether the JPEG compression process can be actually fitted, and the loss of precision points in the JPEG compression process are found, and the prediction fitting matrix is made for the loss of precision points.

When some embodiments of the invention predict and make a fitting, the precision loss of the steganographic quantization matrix after JPEG compression is really predicted, the precision loss is supplemented to the steganographic quantization matrix in advance before the JPEG compression according to the loss value, similarly, a layer of 'protective film' is added to the steganographic quantization matrix, namely, mask processing is carried out, the 'protective film' is lost after the image is subjected to JPEG encoding and decoding, and then the steganographic quantization matrix containing steganographic data is left, so that the storage of a secret key matrix can be omitted, and the operation is simplified.

Step 170: and coding the encrypted steganographic matrix to obtain a steganographic image.

The method 100 is adopted to write the steganographic data into the JPEG image for lossy compression, on one hand, the occupied space of the transmission data is reduced through the lossy compression, on the other hand, the loss value is supplemented in advance through fitting the loss value generated in the lossy compression and decompression processes, so that the data receiver can directly compare the data matrix obtained through decompression with the original quantization matrix to obtain the steganographic data, and the influence of the existence of the loss value on the accuracy of obtaining the steganographic data is avoided. Meanwhile, the steganographic data can be obtained only by simultaneously obtaining the original image, the steganographic image, the quantization rule and the compression rule, and the safety is high.

Fig. 4 shows a flow diagram of a lossy format data extraction method 400 in which an embodiment of the invention can be implemented, applied to a data extractor, the method 400 comprising:

step 410: acquiring a steganographic image, and decoding the steganographic image to determine a steganographic quantization matrix of the steganographic image;

after receiving the steganographic image, the data extractor first converts the steganographic image into a two-dimensional matrix, in a specific manner as described in the foregoing embodiment. And then, based on the two-dimensional matrix corresponding to the steganographic image, obtaining the frequency domain information of the steganographic image through Fourier transform. Specifically, spatial domain data of the steganographic image is converted into frequency domain data through discrete cosine transform.

Step 420: obtaining frequency domain information of an original image, and carrying out data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

the original image is predetermined by the data steganography party and the data extraction party, and the implementation of obtaining the original quantization matrix according to the original image is described in the above embodiments, and is not described herein again.

Step 430: comparing the original quantization matrix with a steganographic quantization matrix of a steganographic image to obtain difference data;

because the steganographic image contains the data to be steganographically written, the steganographically quantized matrix and the original quantized matrix have difference, and the difference data obtained by comparing the original quantized matrix and the steganographically quantized matrix of the steganographic image is the steganographically written data.

In some embodiments of the present invention, step 430 operates to subtract the original quantization matrix from the steganographic quantization matrix of the steganographic image to obtain difference data.

Step 440: and obtaining steganographic data based on the difference data and a preset rule.

The data steganography party uses different preset rules to steganography data, so that the steganography data needs to be obtained according to the preset rules and the difference data when the steganography data is extracted, for example, if the preset rules are a predetermined steganography mode, the steganography data is determined according to the steganography mode and the difference data which are realized in a predetermined manner, and if the steganography mode is carried in a steganography picture, the steganography data is obtained according to the steganography mode and the difference data in the steganography picture.

In the lossy format data extraction method, a data extraction party needs to obtain an original image, a steganographic image, a quantization rule and a compression rule at the same time to obtain steganographic data, because the original image is well agreed by the data steganographic party and the data extraction party and is difficult to obtain by a third party, the quantization rule and the compression rule can also be agreed in advance or recorded in the data transmission process according to needs, and therefore the lossy format data extraction method has high safety.

It should be noted that for simplicity of description, the above-mentioned method embodiments are shown as a series of combinations of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required to practice the invention.

The above is a description of embodiments of the method, and the embodiments of the apparatus are described below to further illustrate the aspects of the present invention.

Fig. 5 shows a block diagram of a device 500 for steganography of lossy format data according to an embodiment of the present invention, as shown in fig. 5, the device 500 comprises:

an information obtaining module 510, configured to obtain data to be steganographically written and an original image; the original image is agreed by a data steganography party and a data extraction party in advance;

a data quantization module 520, configured to determine frequency domain information of the original image, and perform data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

the steganographic data adding module 530 is configured to add to-be-steganographic data to the original quantization matrix according to a preset rule to obtain a steganographic quantization matrix;

a fitting module 540, configured to ensure that the steganographic quantization matrix is fitted to obtain a fitting matrix;

the key obtaining module 550 is configured to perform data quantization on the frequency domain information of the fitting matrix, and compare the frequency domain information with the steganography quantization matrix to obtain a key matrix;

a key adding module 560, configured to add the key matrix to the steganographic quantization matrix to obtain an encrypted steganographic matrix;

and the encoding module 570 is configured to encode the encrypted steganographic matrix to obtain a steganographic image.

It can be understood that each module in the lossy format data steganography apparatus shown in fig. 5 has a function of implementing each step in fig. 1, and can achieve the corresponding technical effect, and for brevity, no further description is given here.

Fig. 6 shows a block diagram of an apparatus 600 for extracting lossy format data according to an embodiment of the present invention, and as shown in fig. 6, the apparatus 600 includes:

the steganographic image quantization module 610 is configured to obtain a steganographic image, decode the steganographic image, and determine a steganographic quantization matrix of the steganographic image;

an original image quantization module 620, configured to obtain frequency domain information of an original image, and perform data quantization on the frequency domain information of the original image to obtain an original quantization matrix;

a comparing module 630, configured to compare the original quantization matrix with a steganographic quantization matrix of a steganographic image to obtain difference data;

and the extracting module 640 is configured to obtain steganographic data based on the difference data and a preset rule.

It can be understood that each module in the lossy format data extracting apparatus shown in fig. 6 has a function of implementing each step in fig. 4, and can achieve the corresponding technical effect, and for brevity, no further description is provided herein.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.

The invention also provides an electronic device, a readable storage medium and a computer program product according to the embodiment of the invention.

FIG. 7 shows a schematic block diagram of an electronic device 700 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

The electronic device 700 comprises a computing unit 701 which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the electronic device 700 can also be stored. The calculation unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

A number of components in the electronic device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the electronic device 700 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

Computing unit 701 may be a variety of general purpose and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 701 performs the various methods and processes described above, such as the method 100 and the method 400. For example, in some embodiments, the

methods

100 and 400 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into RAM 703 and executed by computing unit 701, one or more steps of

methods

100 and 400 described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured by any other suitable means (e.g., by means of firmware) to perform the method 100 and the method 400.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program code, when executed by the processor or controller, causes the functions/acts specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server combining a blockchain.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present invention can be achieved.

The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for steganography of data in a lossy format, comprising:

adding the data to be steganographically written into the original quantization matrix according to a preset rule to obtain a steganographically quantized matrix;

fitting the steganographic quantization matrix to obtain a fitting matrix;

and coding the encrypted steganographic matrix to obtain a steganographic image.

2. The method of claim 1, wherein adding the data to be steganographically written to the original quantization matrix according to a preset rule to obtain a steganographically quantized matrix comprises:

the data steganography side and the data extraction side predetermine a steganography mode of the data to be steganography, and the data to be steganography is added into the original quantization matrix; or the data steganography party determines a steganography mode of the data to be steganographed when performing data steganography, adds the data to be steganographed into the original quantization matrix, and adds the steganography mode of the data to be steganographed into the steganography image.

3. The method of claim 2, wherein the steganographic approach comprises:

4. The method of claim 1, wherein adding the data to be steganographically written to the original quantization matrix according to a preset rule to obtain a steganographically written quantization matrix comprises:

and converting the data to be hidden into binary data.

5. The method of claim 1, wherein the original image is in RGB format, the original quantization matrix and the steganographic quantization matrix are in YUV format, and fitting the steganographic quantization matrix to obtain a fitting matrix comprises: and fitting the steganographic quantization matrix in the YUV format to obtain a fitting matrix in the RGB format.

6. A lossy format data extraction method based on any one of claims 1 to 5, applied to a data extraction side, comprising:

comparing the original quantization matrix with a steganographic quantization matrix of the steganographic image to obtain difference data;

7. A device for steganographically encoding data in a lossy format, comprising:

the steganographic data adding module is used for adding the data to be steganographic data into the original quantization matrix according to a preset rule to obtain a steganographic quantization matrix;

the secret key acquisition module is used for comparing the frequency domain information of the fitting matrix with the steganographic quantization matrix after the data quantization is carried out on the frequency domain information of the fitting matrix to obtain a secret key matrix;

8. A lossy format data extraction apparatus, comprising:

the comparison module is used for comparing the original quantization matrix with the steganographic quantization matrix of the steganographic image to obtain difference data;