CN105719225B - A kind of key recovery method of the LSB Matching steganography based on small echo absolute moment - Google Patents
A kind of key recovery method of the LSB Matching steganography based on small echo absolute moment Download PDFInfo
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- 238000012360 testing method Methods 0.000 claims abstract description 65
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000001914 filtration Methods 0.000 claims description 12
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- 230000009466 transformation Effects 0.000 claims description 6
- 238000001514 detection method Methods 0.000 description 8
- 238000003780 insertion Methods 0.000 description 7
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0021—Image watermarking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2201/00—General purpose image data processing
- G06T2201/005—Image watermarking
- G06T2201/0065—Extraction of an embedded watermark; Reliable detection
Abstract
The invention discloses a kind of key recovery methods of LSB Matching steganography based on small echo absolute moment to perform the following steps in sequence each possible stego-key in key space or key dictionary respectively: A: setting steganography message length estimated valueL, according to each possible stego-keykGenerating length isLTest pathB: the remaining absolute average of small echo absolute moment of all positions in test path in image to be detected is calculated separatelyAnd it is located at the remaining absolute average of small echo absolute moment of all positions outside test path in image to be detected；C: it calculatesWithDifference；D: one or more maximum differences are chosenDoubtful stego-key of the corresponding stego-key as reduction.The present invention can determine doubtful stego-key under the premise of embedded location is only determined by stego-key.
Description
Technical field
The present invention relates to field of information security technology more particularly to a kind of LSB Matching based on small echo absolute moment are hidden
The key recovery method write.
Background technique
Steganography is to be embedded in secret information in the redundancy of the multi-medium datas such as image, video or audio, hidden to realize
Cover a kind of technology of communication.With the development of computer network and multimedia technology, steganography has become information security neck
One of the important technology in domain can be used for the secret communication between personal and enterprise.Concurrently, enterprise staff or government's duty
Internal information may also be hidden in using steganography and seem the multi-medium datas such as normal digital picture, audio or video by member
In leak out, with escape supervision.In numerous steganography methods, LSB matches steganography since it realizes that simple and concealment is strong
The characteristics of, expanded to a variety of different Digital Media, and develop many modified versions to differ from one another.Therefore, right
The evidence obtaining of LSB matching steganography has become one of the research emphasis in evidence obtaining steganalysis direction.
Currently, LSB matches the research of steganography evidence obtaining aspect, not only includes the hidden close image detection of LSB matching steganography, also wraps
Include the estimation of insertion rate and hidden close location estimation of LSB matching steganography.Wherein, the hidden close image detection that LSB matches steganography is current
LSB matches the emphasis that steganography evidence obtaining aspect is studied, and detection method can be divided mainly into two classes: detection method based on generic features and
Detection method based on special characteristic.The former mainly utilizes some general blind Detecting feature (such as co-occurrence matrix) training classifiers real
The hidden close image detection of existing LSB matching steganography, the latter mainly utilize some specific Stego-detection features for LSB matching steganography
(such as histogram feature function and small echo absolute moment) realizes detection.The main method of the insertion rate estimation of LSB matching steganography has most
The maximum-likelihood estimation technique, the method based on adjacent pixel to transfer and method based on machine learning etc..LSB matches the hidden close of steganography
Location estimation method mainly has the hidden close location estimation method based on Bayes and the hidden close location estimation based on small echo absolute moment
Method.
The above method enriches the means of LSB matching steganography evidence obtaining, is mentioned to prevent LSB from matching steganography by criminal's abuse
Technical support is supplied.However, the final purpose of steganography evidence obtaining is to restore the secret information of insertion.And many steganography softwares are embedding
A certain number of pixels will be chosen when entering information according to stego-key with embedding information.Therefore, how correctly to restore steganography close
Key has become a vital link in LSB matching steganography evidence obtaining.
Summary of the invention
The object of the present invention is to provide a kind of key recovery method of LSB Matching steganography based on small echo absolute moment,
Can be in known embedded location selection mechanism, and stego-key is differentiated under the premise of embedded location is only determined by stego-key
The true and false, and determine doubtful stego-key.
The present invention adopts the following technical solutions:
A kind of key recovery method of the LSB Matching steganography based on small echo absolute moment, for key space or close
Each possible stego-key in key dictionary, perform the following steps in sequence respectively:
A: setting steganography message length estimated value L, using known embedded location selection mechanism, according to each possible hidden
It writes key k and generates the test path Path that length is Lk,Pathk=i1i2…iL, wherein i1, i2 ..., iL are respectively according to can
Can stego-key k obtain the 1,2nd ..., L possible embedded locations；
B: the small echo absolute moment for calculating each position in image to be detected using small echo absolute moment residue calculation method is remaining,
Then the remaining absolute average of small echo absolute moment of all positions in test path in image to be detected is calculated separatelyAnd it is located at the remaining absolute average of small echo absolute moment of all positions outside test path in image to be detected
C: the remaining absolute average R of small echo absolute moment for all positions being located in test path is calculatedkIt is surveyed with being located at
Try the remaining absolute average R of small echo absolute moment of all positions outside pathk' difference dk,
D: the difference d corresponding to the multiple possible stego-keys being calculatedkIn, it is maximum to choose one or more
Difference dkDoubtful stego-key of the corresponding stego-key as reduction.
In the step B, the remaining absolute average of small echo absolute moment of all positions in test path
Calculation method it is as follows:
B11: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, hangs down
Straight subband V and diagonal subband D；
B12: it is calculated separately based on N number of various sizes of window each in horizontal subband H, vertical subband V and diagonal subband D
The maximum a-posteriori estimation v of the local variance of position ii, calculation formula is as follows:
WhereinIndicate all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value of square, W ∈ { H, V, D },
B13: setting 0 for low frequency sub-band, carries out to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Quasi-Wiener filtering:
Wherein, RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiSmall echo before indicating filtering
The coefficient of i-th of position of subband W；
B14: by coefficients R obtained in step B13W,iInverse wavelet transform to airspace, using the value of position each after transformation as
The small echo absolute moment residue r of corresponding positioni；
B15: the remaining absolute average of small echo absolute moment of all positions in test path is acquired
In the step B, the remaining absolute average of small echo absolute moment of all positions outside test path
Calculation method it is as follows:
B21: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, hangs down
Straight subband V and diagonal subband D；
B22: it is calculated separately based on N number of various sizes of window each in horizontal subband H, vertical subband V and diagonal subband D
The maximum a-posteriori estimation v of the local variance of position ii, calculation formula is as follows:
WhereinIndicate all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value of square, W ∈ { H, V, D },
B23: setting 0 for low frequency sub-band, carries out to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Quasi-Wiener filtering:
Wherein, wherein RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiBefore indicating filtering
Wavelet sub-band W i-th of position coefficient；
B24: by coefficients R obtained in step B23W,iInverse wavelet transform to airspace, using the value of position each after transformation as
The small echo absolute moment residue r of corresponding positioni；
B25: the remaining absolute average of small echo absolute moment of all positions outside test path is acquired
Level-one wavelet decomposition is carried out to image to be detected using 8-tap Daubechies filter.
Each position in horizontal subband H, vertical subband V and diagonal subband D is calculated separately using 4 various sizes of windows
The maximum a-posteriori estimation v of the local variance of ii。
The present invention firstly generates the test road that length is L to each possible key in key space or key dictionary
Then diameter calculates separately all positions in test path in image to be detected using small echo absolute moment residue calculation method
The remaining absolute average of small echo absolute momentAnd it is located at the small echo of all positions outside test path in image to be detected
The remaining absolute average of absolute momentFinally according to their differenceIt determines and differentiates the true of stego-key
Puppet greatly improves the efficiency and accuracy of the judgement of the stego-key true and false.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Specific embodiment
The present invention is made with detailed description below in conjunction with drawings and examples:
As shown in Figure 1, the key recovery method of the LSB Matching steganography of the present invention based on small echo absolute moment,
For each possible stego-key in key space or key dictionary, it perform the following steps in sequence respectively:
A: setting steganography message length estimated value L, using known embedded location selection mechanism, according to each possible hidden
It writes key k and generates the test path Path that length is Lk,Pathk=i1i2…iL, wherein i1,i2,…,iLRespectively according to possible
Stego-key k obtain the 1,2nd ..., L possible embedded locations.
B: the small echo absolute moment for calculating each position in image to be detected using small echo absolute moment residue calculation method is remaining,
Then the remaining absolute average of small echo absolute moment of all positions in test path in image to be detected is calculated separatelyAnd it is located at the remaining absolute average of small echo absolute moment of all positions outside test path in image to be detected
In the step B, the remaining absolute average of small echo absolute moment of all positions in test path
Calculation method it is as follows:
B11: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, hangs down
Straight subband V and diagonal subband D；8-tap Daubechies filter can be used in filter.
B12: it is calculated separately based on N number of various sizes of window each in horizontal subband H, vertical subband V and diagonal subband D
The maximum a-posteriori estimation v of the local variance of position ii, calculation formula is as follows:
WhereinIndicate all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value of square, W ∈ { H, V, D },In the present embodiment, 4 various sizes of windows can be used.
B13: setting 0 for low frequency sub-band, carries out to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Quasi-Wiener filtering:
Wherein, RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiSmall echo before indicating filtering
The coefficient of i-th of position of subband W；
B14: by coefficients R obtained in step B13W,iInverse wavelet transform to airspace, using the value of position each after transformation as
The small echo absolute moment residue r of corresponding positioni；
B15: the remaining absolute average of small echo absolute moment of all positions in test path is acquired
In the step B, the remaining absolute average of small echo absolute moment of all positions outside test path
Calculation method it is as follows:
B21: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, hangs down
8-tap Daubechies filter can be used in straight subband V and diagonal subband D, filter；
B22: it is calculated separately based on N number of various sizes of window each in horizontal subband H, vertical subband V and diagonal subband D
The maximum a-posteriori estimation v of the local variance of position ii, calculation formula is as follows:
WhereinIndicate all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value of square, W ∈ { H, V, D },In the present embodiment, 4 various sizes of windows can be used.
B23: setting 0 for low frequency sub-band, carries out to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Quasi-Wiener filtering:
Wherein, RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiSmall echo before indicating filtering
The coefficient of i-th of position of subband W；
B24: by coefficients R obtained in step B23W,iInverse wavelet transform to airspace, using the value of position each after transformation as
The small echo absolute moment residue r of corresponding positioni；
B25: the remaining absolute average of small echo absolute moment of all positions outside test path is acquired
C: the remaining absolute average of small echo absolute moment for all positions being located in test path is calculatedIt is surveyed with being located at
Try the remaining absolute average of small echo absolute moment of all positions outside pathDifference dk,
D: the difference d corresponding to the multiple possible stego-keys being calculatedkIn, it is maximum to choose one or more
Difference dkDoubtful stego-key of the corresponding stego-key as reduction.
It is absolute due to being not embedded into the remaining absolute mean of small echo absolute moment of information position and the small echo of embedding information position
There are significant differences for the remaining absolute mean of square, therefore the present invention is located at the small echo of all positions in test path by calculating
The remaining absolute average of absolute momentIt is remaining absolutely average with the small echo absolute moment for all positions being located at outside test path
ValueDifference dk, carry out the judgement of the stego-key true and false.
For pseudo- stego-key, randomly selected in hidden close image since the test path generated in step A is equivalent to, institute
Ratio shared by the position of information and the outer embedding information of test path are embedded in the test path of generation with pseudo- stego-key
Position shared by ratio it is approximately equal with the insertion rate in whole picture image to be detected.Therefore, for pseudo- stego-key, road is tested
In diameter and the difference of ratio shared by the position of the outer embedding information of test path is approximately 0.
And for true stego-key, then there is following three situation:
1) when the test path length of generation is less than embedding information length, all positions on test path are respectively positioned on embedding
Entering in the position of information, i.e. the ratio that the position of embedding information accounts for test path is 1, and then comprising being partially submerged into outside test path
The position of information, the ratio that the position for being partially submerged into information outside test path accounts for test path external position quantity are less than whole
Insertion rate p (0 < p < 1) in width image.Therefore, ratio shared by the position of embedding information in test path and outside test path
Difference is greater than 1-p.
2) when the test path length of generation is equal to embedding information length, all positions on test path are respectively positioned on embedding
Enter in the position of information, i.e. the ratio that the position of embedding information accounts for test path is 1, and outside test path does not include any insertion
It is 0 that insertion information bit, which sets and accounts for the ratio of test path external position quantity, outside the position of information, i.e. test path.Therefore, road is tested
In diameter and the difference of ratio shared by the position of the outer embedding information of test path is equal to 1.
3) when the test path length of generation is greater than embedding information length, comprising all embedding informations on test path
Position, therefore the position of embedding information accounts for the p that is greater than of the ratio of test path, and outside test path do not include any embedding information
Position, i.e., be embedded in information bit outside test path and set that account for the ratio of test path external position quantity be 0.Therefore, in test path
The difference of ratio shared by position with embedding information outside test path should be greater than p.
In conclusion for true stego-key, ratio shared by the interior position with the outer embedding information of test path of test path
Difference be greater than 0 certainly, this makes the remaining absolute average of small echo absolute moment in test pathIt is likely to be greater than test road
The remaining absolute average of the outer small echo absolute moment of diameterTherefore, the present invention can be remaining according to small echo absolute moment in test path
Absolute averageWith the remaining absolute average of small echo absolute moment outside test pathDifference dkIt is true to carry out stego-key
Pseudo- judgement, is inferred to doubtful stego-key.
Claims (5)
1. a kind of key recovery method of the LSB Matching steganography based on small echo absolute moment, which is characterized in that for key sky
Between or key dictionary in each possible stego-key, perform the following steps in sequence respectively:
A: being arranged steganography message length estimated value L, close according to each possible steganography using known embedded location selection mechanism
Key k generates the test path Path that length is Lk,Pathk=i1i2…iL, wherein i1,i2,…,iLRespectively according to possible hidden
The key k is obtained the 1,2nd is write ..., L possible embedded locations；
B: the small echo absolute moment for calculating each position in image to be detected using small echo absolute moment residue calculation method is remaining, then
Calculate separately the remaining absolute average of small echo absolute moment for being located at all positions in image to be detected in test pathWith
And it is located at the remaining absolute average of small echo absolute moment of all positions outside test path in image to be detected
C: the remaining absolute average of small echo absolute moment for all positions being located in test path is calculatedRoad is tested with being located at
The remaining absolute average of small echo absolute moment of all positions outside diameterDifference dk,
D: the difference d corresponding to the multiple possible stego-keys being calculatedkIn, choose one or more maximum difference dk
Doubtful stego-key of the corresponding stego-key as reduction.
2. the key recovery method of the LSB Matching steganography according to claim 1 based on small echo absolute moment, feature
It is, in the step B, the remaining absolute average of small echo absolute moment of all positions in test path's
Calculation method is as follows:
B11: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, vertical son
Band V and diagonal subband D；
B12: each position in horizontal subband H, vertical subband V and diagonal subband D is calculated separately based on N number of various sizes of window
The maximum a-posteriori estimation v of the local variance of ii, calculation formula is as follows:
WhereinIndicate square of all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value, W ∈ { H, V, D },
B13: setting 0 for low frequency sub-band, carries out quasi- to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Wiener filtering:
Wherein, RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiWavelet sub-band W before indicating filtering
I-th of position coefficient；
B14: by coefficients R obtained in step B13W,iInverse wavelet transform is to airspace, using the value of position each after transformation as correspondence
The small echo absolute moment residue r of positioni；
B15: the remaining absolute average of small echo absolute moment of all positions in test path is acquired
3. the key recovery method of the LSB Matching steganography according to claim 1 based on small echo absolute moment, feature
It is, in the step B, the remaining absolute average of small echo absolute moment of all positions outside test pathMeter
Calculation method is as follows:
B21: carrying out level-one wavelet decomposition to image to be detected using filter, obtains low frequency sub-band, horizontal subband H, vertical son
Band V and diagonal subband D；
B22: each position in horizontal subband H, vertical subband V and diagonal subband D is calculated separately based on N number of various sizes of window
The maximum a-posteriori estimation v of the local variance of ii, calculation formula is as follows:
WhereinIndicate square of all coefficients in N × N neighborhood in wavelet sub-band W centered on the coefficient of i-th of position
Mean value, W ∈ { H, V, D },
B23: setting 0 for low frequency sub-band, carries out quasi- to each coefficient of horizontal subband H, vertical subband V and diagonal subband D
Wiener filtering:
Wherein, wherein RW,iIndicate the coefficient of i-th of position by filtered wavelet sub-band W, WiSmall echo before indicating filtering
The coefficient of i-th of position of subband W；
B24: by coefficients R obtained in step B23W,iInverse wavelet transform is to airspace, using the value of position each after transformation as correspondence
The small echo absolute moment residue r of positioni；
B25: the remaining absolute average of small echo absolute moment of all positions outside test path is acquired
4. the key recovery method of the LSB Matching steganography according to claim 2 or 3 based on small echo absolute moment,
It is characterized in that: level-one wavelet decomposition is carried out to image to be detected using 8-tap Daubechies filter.
5. the key recovery method of the LSB Matching steganography according to claim 2 or 3 based on small echo absolute moment,
It is characterized in that: calculating separately each position in horizontal subband H, vertical subband V and diagonal subband D using 4 various sizes of windows
Set the maximum a-posteriori estimation v of the local variance of ii。
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| CN111047497B (en) * | 2019-12-24 | 2022-10-04 | 中国人民解放军战略支援部队信息工程大学 | JPEG image steganography information positioning method based on same-frequency sub-image filtering |
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Effective date of registration: 20201023 Address after: 450001 No. 62 science Avenue, hi tech Zone, Henan, Zhengzhou Patentee after: Information Engineering University of the Chinese People's Liberation Army Strategic Support Force Address before: 405, 450001, 62, science Avenue, Zhengzhou hi tech Development Zone, Henan, China Patentee before: Yang Chunfang |
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