CN111079573A - Anti-counterfeiting encryption method based on image random scrambling technology - Google Patents
Anti-counterfeiting encryption method based on image random scrambling technology Download PDFInfo
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Abstract
The invention discloses an anti-counterfeiting encryption method based on an image random scrambling technology, and belongs to the technical field of encryption and anti-counterfeiting. The invention carries out random spatial scrambling without any rule on the information in the image, and can greatly improve the security of encryption because the spatial structure information is difficult to crack; moreover, random spatial scrambling can be coupled with masking, further improving reliability. The existing method can not leave out passwords, character strings and the like, and the encrypted and anti-counterfeiting signals are signals without space-time structures. The anti-counterfeiting encryption method completely breaks away from the existing encryption and anti-counterfeiting framework, utilizes the signal of the image space structure to realize encryption and anti-counterfeiting information, and is an encryption and anti-counterfeiting method in a brand new sense.
Description
Technical Field
The invention belongs to the field of encryption and anti-counterfeiting, and particularly relates to an anti-counterfeiting encryption method based on an image random scrambling technology.
Background
The greatest advantage of digital technology is the extremely high stability, which allows transmission, copying and storage without loss, which is the greatest advantage, but also entails great difficulties-its security is really too poor. The problems of digital information encryption and anti-counterfeiting become very difficult to solve. At present, network disputes and network crimes occur in large quantity. Along with the technical development, the crime making cost is greatly reduced, people who do not know the network can buy the crime making equipment in the market very cheaply, and the crime making operation is also convenient. The number of the counter persons is increased, and network encryption and network anti-counterfeiting become problems in the network.
The anti-counterfeiting technology of the bitcoin can be calculated as the most secure means. It uses RSA or ECC encryption technique to replace anti-fake actually, because RSA and ECC are not decoded, so it makes the bit coin the safest measure, although RSA and ECC are not decoded, it can use exhaustion method to decode, in order to improve RSA and ECC reliability, it can only increase its reliability by increasing calculated digit, now RSA has increased to one thousand to two thousand, we use 64 digit double precision personal computer, it is inconvenient to use this computer to calculate one thousand digit operation. Although the number of bits of the ECC is only 200-300 bits, the ECC is equivalent to the encryption strength of RSA1000 bits due to high computational complexity. The implementation of public password encryption in a common PC is still cumbersome and time consuming, and is more difficult to implement especially on a mobile phone. The blockchain technology is more popular recently, but the core part of the blockchain has public codes, so it has the same weaknesses of RSA and ECC.
At present, no technology such as bitcoin and blockchain technology are adopted in electronic commerce, namely electronic invoice and electronic payment (indeed, the operation speed problem is still not solved in the current effort).
The existing e-commerce uses security technologies such as: the random sequence is composed of numbers, character codes and the like and used as a password, the longer the sequence is, the higher the safety level is, the longer the sequence is, the higher the safety level is, the sequence is difficult to be memorized, particularly, many people are easy to memorize, the birthday of the people is often used as the password, or the birthdays of several family people or various data related to the people are used as the password, and the people are close to the habits of the people and know the habits of the people, so that the cracking range of the password is greatly reduced, the reliability of the password is greatly deteriorated, therefore, the method is further adopted at present to improve the reliability by adding more measures, such; transmitting the authentication code (such as a telephone short message, a network Email and the like) by multiple channels; a two-dimensional bar code; the mobile phone number is used as a confirmation basis and the like. Careful analysis of these methods is not very reliable, but several methods are used, just to add some sense of security.
The methods listed above are all the bases of numbers and codewords, and are independent of the image signal having a spatial structure. The technology of the prior art, no matter the technology of hardware and software is developed, the technologies of transmission, storage, copying and the like of the image are well developed, so that the technology of fully utilizing the characteristics of the digital image to realize encryption and anti-counterfeiting appears to be easy to realize, and the technology in the aspect is expected to greatly improve the encryption and anti-counterfeiting performance.
Disclosure of Invention
The invention aims to overcome the defects of the anti-counterfeiting encryption method in the prior art in terms of safety and reliability, and provides the anti-counterfeiting encryption method based on the image random scrambling technology.
The invention adopts the following specific technical scheme:
in a first aspect, the present invention provides an anti-counterfeit encryption method based on an image random scrambling technology, which comprises the following steps:
s1: information to be encrypted is superposed on a first image with unique biological characteristic information of a sender to obtain a second image;
s2: carrying out random spatial scrambling on pixels in the second image, wherein the random spatial scrambling is to carry out random position exchange on pixel distribution in space under the condition of keeping pixel values unchanged, so that a third image is obtained after the image is converted into a visual random scatter diagram;
s3: after the receiving party obtains the third image, restoring the third image according to the reverse process of the random spatial scrambling to obtain a second image;
s4: and the receiver acquires the unique biological characteristic information used for verification by the sender, compares the unique biological characteristic information with the unique biological characteristic information recorded in the second image, and reads the encrypted information from the second image if the unique biological characteristic information passes the comparison.
In a preferred implementation manner of the first aspect, in S1, the second image is masked before being randomly spatially scrambled, each pixel value in the second image is calculated with the mask image according to a predetermined rule, and then a fourth image is formed from the calculation result and is used as a new second image to be randomly spatially scrambled in S2, where the fourth image is a visually random scatter diagram.
Preferably, as two implementation manners of the first aspect, the first image with the unique biometric feature information of the sender is a photograph with a face of the sender.
As a preferable mode of the above-mentioned first aspect, the mask processing method includes: acquiring a mask image with the same size as the processed image, performing mathematical operation on the pixel values of corresponding pixels in the processed image and the mask image according to a predetermined rule, and recording the operation result value in a corresponding position of a fourth image.
Further, in the mask processing, if the arithmetic result value after the mathematical operation exceeds the size limit of the image pixel value, the fourth image is divided into a main image and an auxiliary image, the main image is recorded with a threshold value of the pixel value, and the auxiliary image is recorded with a difference value between the arithmetic result value and the threshold value.
As a preferable mode of the two implementation modes of the first aspect, the unique biological feature information used by the sender for verification is obtained by a real-time verification mode, and is preferably a real-time video face authentication mode.
In a preferred embodiment of the first aspect, the image is a monochrome image or a color image.
Preferably, in two implementations of the first aspect, the image pixel value is 8 bits, 24 bits, or other bits.
Compared with the prior art, the invention has the following beneficial effects:
1) the existing method can not leave out passwords, character strings and the like, and the encrypted and anti-counterfeiting signals are signals without space-time structures. The anti-counterfeiting encryption method completely breaks away from the existing encryption and anti-counterfeiting framework, utilizes the signal of the image space structure to realize encryption and anti-counterfeiting information, and is an encryption and anti-counterfeiting method in a brand new sense.
2) The invention carries out random spatial scrambling without any rule on the information in the image, and can greatly improve the security of encryption because the spatial structure information is difficult to crack; moreover, random spatial scrambling can be coupled with masking, further improving reliability. The invention can realize the decryption without using an exhaustion method.
3) In the invention, the original image is provided with the unique biological characteristic information of the sender, and the unique biological characteristic information of the sender can be used for anti-counterfeiting verification to prevent the false use of other people.
3) The digital image has the greatest characteristic that the image can be modified at will, such as changing one person's head portrait, separating characters from the image, or modifying a signature, and the like, and the modification can be realized in a manner of ' seamless ' within a range which can be recognized by naked eyes. However, because the invention adopts the random scrambling method, the pixel points at any local position of the original image can be dispersed at any position of the scrambled image after scrambling, and if the random small area of the scrambled image needs to be changed. Is reflected in the whole image, i.e. any minor modifications can be found quickly, which substantially prevents local modifications of the image.
Drawings
FIG. 1 is a schematic view of a first image in example 1;
FIG. 2 is a second image diagram in example 1;
FIG. 3 is a schematic view of a third image in example 1;
fig. 4 is a diagram illustrating a fourth image in embodiment 2.
Detailed Description
The invention will be further elucidated and described with reference to the drawings and the detailed description.
Example 1:
the invention discloses an anti-counterfeiting encryption method based on an image random scrambling technology, which comprises the following specific steps:
s1: first, a first image with unique biological characteristic information of a sender is obtained, wherein the unique biological characteristic information of the sender can be unique biological identification characteristic information of a face, a fingerprint, an iris and the like of the sender. In the present invention, it is preferable to use a photograph with the face of the sender, as shown in fig. 1, in view of the convenience of acquisition. The information to be encrypted, which is required to be sent by the sender, can be directly written on the first image to obtain a second image. Taking the payment process as an application scenario as an example, the writable encryption information is corresponding payment information, and the second image is shown in fig. 2, although the specific encryption information may be changed according to the application scenario. It should be noted that in this step, the position and size of the written encrypted information should be properly controlled so as not to destroy the reading of the unique biometric feature information.
S2: and randomly spatially scrambling the pixels in the second image, wherein the random spatial scrambling in the present invention refers to randomly disordering spatial positions of the pixels, that is: the pixel distribution is spatially subjected to random position swapping while keeping the pixel values unchanged, and the image is converted into a visually random scatter diagram, thereby obtaining a third image, as shown in fig. 3. The random spatial scrambling may be implemented in a variety of ways, such as performing matrix operations on pixel lattices in the image, where the matrix operations may facilitate subsequent inverse operations to extract information.
The third image may be used as a carrier of encrypted information for delivery to a recipient of the information. Because the third image is a random image, if a person who is not aware of the scrambling process cannot distinguish the image with the information, and even if the person knows the image with the information, the person does not know how to extract the information, so that the reliability of encryption can be fully ensured.
S3: and after the receiving party acquires the third image, restoring the third image according to the reverse process of the random spatial scrambling to obtain a second image. The second image at this time may be directly read with the encrypted information described by the sender. However, the third image may be stolen or tampered during transmission, so that the third image needs to be subjected to the next anti-counterfeiting verification.
S4: the process of anti-counterfeiting verification comprises the following steps: the receiver requests the sender for the actual unique biometric information for verification. And the second image is obtained by writing secret information on the first image, so that the second image also carries the unique biological characteristic information of the sender. After the receiver acquires the unique biological characteristic information used for verification by the sender, the unique biological characteristic information can be compared with the unique biological characteristic information recorded in the second image, if the unique biological characteristic information passes the comparison, the image is shown to be actually sent by the sender, and at the moment, the true encrypted information can be successfully read from the second image.
It should be noted that, in this step, the method for the receiving side to obtain the unique biometric feature information used by the sending side for authentication may be various, and the specific requirement is determined according to the security requirement of the sending side for this operation. Taking a payment scenario as an example, the sender may select multiple authentication methods: 1) reserving the unique biological characteristic information of the receiver, and directly calling the reserved information for comparison after the receiver restores to obtain a second image; 2) after the receiver restores to obtain the second image, the receiver informs the sender to request the sender to send an image with own unique biological characteristic information for verification; 3) and after the receiver restores the second image, the receiver informs the sender to request the sender to start online real-time authentication, the authentication can be further dynamic, and the image with the own unique biological characteristic information is obtained through the real-time authentication. In the three verification modes, the safety factor 3) >2) >1) and the complexity is 3) >2) >1, so that the corresponding authentication mode can be automatically adjusted according to the requirements of encryption and the payment amount.
Example 2:
on the basis of the embodiment 1, the invention can further set a mask processing mode to carry out secondary encryption, thereby preventing exhaustive cracking.
Due to the irregularity of the image random spatial scrambling in the embodiment 1, the regularity cannot be found to crack the image. However, the method can be cracked by an exhaustion method, if one image has n pixel points in total, the method takes a mathematical 'full arrangement method' to obtain n! A possible image, n! One possible image is determined to have an original image, so that the purpose of cracking is achieved. To prevent this, the invention employs "masking" the second image after it has been created to make it a scattergram of all random scatters. Even if a real second image is found, the second image is visually a random scatter diagram, and cannot be distinguished from other images, and real secret information cannot be acquired.
Specifically, after the step S1 is executed, the masking process is performed on the second image before the random spatial scrambling in step S2, where the masking process includes: after each pixel value in the second image is operated with the mask image according to a predetermined rule, a fourth image is formed from the operation result, and the fourth image is a visually random scatter diagram, as shown in fig. 4. This fourth image is randomly spatially scrambled as a new second image at S2, i.e. the scrambled image at S2 is actually the fourth image.
The mathematical operation of the second image with the mask image requires a specific design, since the fourth image needs to be guaranteed to be a visually random scatter diagram. The mathematical operation can be simply added or subtracted, and can also be any functional relation f (y)i,wi) And are not intended to be limiting.
Example 3:
in this embodiment, on the basis of embodiment 2, in order to prevent a possible disclosure from being generated by using the same image multiple times, a plurality of first images may be stored in advance in the mobile device, and one of the first images is selected for encryption each time. Therefore, the problem of false-proof encryption failure caused by the fact that a certain first image is divulged can be prevented.
Digital images have many advantages and ensure that the images are not damaged during transmission, storage and copying. But the image is also easy to be modified, for example, one person head portrait is changed into another person head portrait, writing or signature in the image is also easy to be modified, and the image can be modified to be seamless. However, the invention proposes a method of random spatial scrambling, that is, each pixel of the image is randomly moved in the image space, so that only the image fully covered with the pockmarks is seen on the picture after the original clear image is scrambled. Because all pixel points of any small area in the original image can be dispersed in the whole scrambled image after random spatial scrambling, if we remove any small part of the image after scrambling, when the image is restored to the original image, at least part of the image in the whole area can be changed. Whether tampering occurs can be identified by comparing the two images, which ensures that the images can be found when being segmented or modified randomly. Therefore, the image and the characters can not be separated or replaced at will, and the reliability is improved.
The above embodiments 1 to 3 are all based on the method of random spatial scrambling to perform the anti-counterfeiting encryption transmission on the secret information. The blockchain technology is hot at present, seems to occupy the whole digital currency market and the e-commerce market, but in fact, the core part of the blockchain is also public passwords, so that the blockchain technology also has the same defects as RSA or ECC. Blockchains also require multipoint contacts, greatly increasing network traffic and time. The method of the invention can avoid the defects and is more suitable for application in the fields of frequently used electronic commerce, mobile payment and the like.
In the following, the present invention is described with several examples in combination with application scenarios of payment awareness, so as to facilitate better understanding of the present invention by those skilled in the art.
The use scenario is as follows:
1) using the object:
sender A- -user
Receiver B- -Bank (or other intermediary deposit mechanism, such as a third party payment platform)
2) Specific behaviors: a is to make a check or send a deposit request to bank B, which pays the other party, i.e. payee C
3) Preparing: a goes to B in advance, the photo, signature and the like are given to B, B puts the photo, the signature, the character string and the like together to form a picture T1(T1Which may be black and white or color images, and the pixels may be 8 bits, 24 bits, and other various numbers of bits). Then to T1And performing random spatial scrambling. The image after "scrambling" is T10. This makes A, B collectively aware of the scrambling algorithm.
The "scrambling" is to scramble all the pixel positions in the original image from new arrangement so that the original image becomes a dot-and-dot-pattern.
Suppose a graph T1Becomes T after random spatial scrambling10,T1Any one pixel is xi(ai,bi) Wherein (a)i,bi) Is a pixel xiIs detected by the position of the coordinates of the (c),
suppose again that image T10Any one pixel is yi(ai,bi) It is related to xi(ai,bi) The points correspond.
Now, how to perform the "random spatial scrambling":
first to T1All pixels in the two-dimensional space are queued for line-by-line scanning, making the two-dimensional image a one-dimensional sequence string.
x1,x2,…,xi…,xm(1)
Formula (1) shows scheme T1Consisting of m pixels in total.
Also available is T10Series of graphs
y1,y2,…,yi,…,ym(2)
Equations (2) and (1) indicate that the two image pixels before and after scrambling are identical (both M).
"random spatial scrambling" can be represented by a correlation matrix (as in the correlation matrix in system theory).
Assuming the following holds:
in the formula (3), the unit matrix is used to establish the following formulas
x1＝y1；x2＝y2；......；xi＝yi；......；xm＝ym。
The pixel value and the spatial structure in the image are kept the same and are not changed after the unit array is acted.
The scrambling process is illustrated next:
for convenience of explanation, assume that m is 5
Now we want to refer to x2And x5And (5) changing the position. Can be realized according to the relation of equation (4):
according to the formula (4), the following formulae can be obtained,
y1＝x1y2＝x5y3＝x3y4＝x4y5＝x2
this means that the pixel value x is influenced by equation (4)2And x5The swap is realized.
In the same way, two points can be randomly selected for conversion by using the 'correlation array', so that the aim of image scrambling is fulfilled. Whatever the law and method used to "scramble" it can eventually be expressed by equation (4). Of course, the scrambling method does not need to take two numbers to replace in pairs, and the transposition can be performed by using 3 or more pixels in turn, so long as the 'correlation matrix' is adjusted correspondingly.
When the reverse process reduction needs to be carried out on the random space scrambling, the inverse operation only needs to be carried out according to the matrix operation, and the inverse operation is recorded as the inverse scrambling algorithm.
Application example 1
A is taken from the photo and added with payment information characters (including the amount of money paid to a person or unit, the collection account number, the added payment date and signature, and the specific payment information can be adjusted) to form T1Then T is put1Is turned into T through random scrambling10Sending to B, B using inverse scrambling algorithm to process T10Is restored to T1. B sees T1The face photo can simultaneously acquire the image sent by the A or the real-time video head portrait, verify the authenticity and simultaneously watch the T1Time of write-in (guarantee T)1Received within the effective time), can press T after no error after confirmation1The contents of the above payment information are described to execute payment and pay to C.
Application example 2
A is taken from the photo, and then the characters of payment information (including the amount of money paid to a person or unit, the account number of the collection, the date and the signature of the payment, and the specific payment information can be adjusted) form T1Then handle T1Masking to form T11The graph becomes T through random spatial scrambling110Sending to B, B using inverse scrambling algorithm to process T110Is restored to T11. Handle T11Performing reverse mask treatment to make T11Becomes T1And B sees T1The picture A and the real-time video head portrait are simultaneously obtained, the authenticity is verified, and the T is simultaneously seen1Time of write-in (guarantee T)1Received within the effective time), can press T after no error after confirmation1The contents of the above payment information are described to execute payment and pay to C.
The masking process is to superimpose a layer of noise image on the original image to submerge the image in the noise. This noisy image is called "masking" of the imageFilm ", or mask F. This process is referred to as a "masking" process. Specifically, the pixel and T in the mask image F1The pixel values of the corresponding points are added (or subtracted) to form new pixel values, and the image formed by the pixels is the image T after the mask is added11。
The masking process is performed by adding or subtracting point by point (or by performing an arbitrary function operation on f (y)i,wi) Wherein y isiIs T1Point of (5), wiIs the corresponding point in F). When applying a mask, several situations arise, and there are 3 treatment methods:
a) when the sum of the pixel values of the two points is greater than the maximum pixel value (taking a black-and-white image as an example, the gray scale value is maximum), let T be assumed1The middle pixel value is yijThe corresponding pixel in the mask F is wij，wij+yij＝M+zijWhere M is the pixel maximum, zijIs the partial value exceeded. Writing M at T11At the corresponding point of (2), z isijWritten in another image F1At the corresponding point of (a). T is11How many points of M are. At F1How many pixels there are, F1The other dots are blank. Handle T11And F1And simultaneously to B.
b) Assuming the mask is subtracted, there is no point of maximum M, but a negative number appears.
yij-wij＝0-zijWrite 0 at T11At the corresponding point of (2), z isijWritten in another image F1At a corresponding point of (1), T101In several numbers 0, in F1In which there are several pixels, and finally T11And F1And simultaneously to B.
c) The mask method is modified, when two pixels are added (or subtracted), the pixel value of the corresponding point of the image F can be properly corrected when an over value (or a negative value) occurs (the anti-positive F is noise), so that the pixel value is not over value (or a negative value is not generated). Thus F becomes F'. Mask F is replaced by F'. When transmitting, subtracting F and F 'point by point to obtain graph F' and graph T11To the other party. The other side knows F 'and the original F, and also knows F'.
The above-mentioned method only uses simple addition and subtraction method, and also can use arbitrary functional relation f (y)i,wi) Is represented by f (y)i,wi) Greater than M and less than 0 correspond to the same treatment as greater than M in addition and less than 0 in subtraction.
The above embodiments and application examples may be implemented on a mobile device, and for example, the identification process of biometric information, the masking process, the random spatial scrambling and the corresponding restoration process, etc. may all be implemented by an algorithm. Of course, the method may be assisted by human intervention, and is not limited thereto.
In the above embodiments and application examples, all the images may be color images, black-and-white images, and grayscale images, as long as they are consistent. That is, the method can be used on black-and-white images as well as on color images, except that the gray values are changed to color pixel values. In addition, the pixel values of the image may be 8-bit, 24-bit, or other number of bits color, or other number of bits image.
In the above embodiments and application examples, the encrypted information may be characters, patterns such as two-dimensional codes and bar codes, or other pictographic elements, as long as both can recognize the meaning. In addition, for the writing process of the information on the image, the information can be input by a keyboard, namely, the information can be input by handwriting, or the information can be input from other systems, and other superposition methods can be adopted, as long as the information can be added to the image.
In the above embodiments and application examples, the scrambling process is not limited to matrix operation, and any form capable of realizing pixel position conversion may be adopted. For example, tabular or other forms may also be used.
The above-described embodiments are merely preferred embodiments of the present invention, which should not be construed as limiting the invention. Various changes and modifications may be made by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present invention. Therefore, the technical scheme obtained by adopting the mode of equivalent replacement or equivalent transformation is within the protection scope of the invention.
Claims (8)
1. An anti-counterfeiting encryption method based on an image random scrambling technology is characterized by comprising the following steps:
s1: information to be encrypted is superposed on a first image with unique biological characteristic information of a sender to obtain a second image;
s2: carrying out random spatial scrambling on pixels in the second image, wherein the random spatial scrambling is to carry out random position exchange on pixel distribution in space under the condition of keeping pixel values unchanged, so that a third image is obtained after the image is converted into a visual random scatter diagram;
s3: after the receiving party obtains the third image, restoring the third image according to the reverse process of the random spatial scrambling to obtain a second image;
s4: and the receiver acquires the unique biological characteristic information used for verification by the sender, compares the unique biological characteristic information with the unique biological characteristic information recorded in the second image, and reads the encrypted information from the second image if the unique biological characteristic information passes the comparison.
2. The image stochastic scrambling technique-based anti-counterfeit encryption method of claim 1, wherein in S1, the second image is masked before being randomly spatially scrambled, after each pixel value in the second image is operated with the mask image according to a predetermined rule, a fourth image is formed from the operation result and is used as a new second image to be randomly spatially scrambled in S2, and the fourth image is a visually random scatter diagram.
3. The anti-counterfeiting encryption method based on the image random scrambling technology as claimed in claim 1 or 2, wherein the first image with the unique biological characteristic information of the sender is a photo with the face of the sender.
4. An anti-counterfeiting encryption method based on the image random scrambling technology according to claim 2, wherein the mask processing method comprises the following steps: acquiring a mask image with the same size as the processed image, performing mathematical operation on the pixel values of corresponding pixels in the processed image and the mask image according to a predetermined rule, and recording the operation result value in a corresponding position of a fourth image.
5. The anti-counterfeiting encryption method based on the image random scrambling technology as claimed in claim 1 or 2, wherein the unique biological characteristic information used for verification by the sender is obtained by means of real-time verification.
6. An anti-counterfeiting encryption method based on image random scrambling technology according to claim 5, characterized in that the real-time verification mode is preferably real-time video face authentication.
7. An anti-counterfeiting encryption method based on the image random scrambling technology as claimed in claim 1 or 2, characterized in that the image is a black-and-white image or a color image.
8. An anti-counterfeiting encryption method based on an image random scrambling technology as claimed in claim 1 or 2, characterized in that the image pixel value is 8 bits, 24 bits or other bits.
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| PCT/CN2020/131658 WO2021104344A1 (en) | 2019-11-29 | 2020-11-26 | Anti-counterfeiting and encryption method based on random image scrambling technique |
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| CN115297221B (en) * | 2022-09-29 | 2022-12-23 | 南通德辰智能科技有限公司 | Image encryption method based on pixel ring scrambling |
| CN116915508B (en) * | 2023-09-13 | 2023-12-12 | 宜兴启明星物联技术有限公司 | Channel dynamic encryption method in communication process |
| CN117579866B (en) * | 2023-11-23 | 2024-05-10 | 江苏亿通高科技股份有限公司 | Smart city monitoring image safety transmission method based on 5G communication |
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