CN113992326B - Non-interactive image editing validity detection method based on aggregation algorithm - Google Patents

Abstract

The invention relates to an image editing detection method based on an aggregation algorithm, which includes: on the basis of public key cryptography, optimize the aggregator in cryptography, realize an auditable aggregator, and combine it with digital signature technology, through the The image is preprocessed and hashed based on the editing rules to generate a hash set, and then the hash set is aggregated with the user's public key to generate an editing license for the image user. After the image user holds the editing license, he edits the image and uses the user's private key to calculate additional evidence for the edited image. After receiving the new image, the verifier verifies whether the editing of the new image is legally authorized according to the editing license and additional evidence. Using the above technical solutions can simultaneously detect the legality of the editing user's operation and identity, which not only ensures the security of the image application, but also makes the operation efficient and convenient, which is helpful for the image receiver to quickly verify whether the received image involves infringement.

Description

Non-interactive image editing legitimacy detection method based on aggregation algorithm

technical field

The invention relates to the field of multimedia information security, in particular supports an image verification party to verify the legality of image editing, and specifically relates to a non-interactive image editing legality detection method based on an aggregation algorithm.

Background technique

Image copyright refers to an exclusive right that is automatically assigned to the creator when the image is created, and this right empowers the image copyright owner (or creator) to decide how to use and process the image. The Intellectual Property Law expressly stipulates that no one may steal, copy or sell other people's works without the permission of the copyright owner. Once an infringement occurs and is identified by a trustworthy institution, the infringed can claim his rights through legal means and request the infringer to make corresponding economic compensation. Although there is legislative protection, infringements are still repeatedly prohibited. The main reason is that the process of identifying infringements is complicated, the time for obtaining evidence is long and the cost is high, and the process of claiming rights is not easy for the infringed.

Ideally, image users need to obtain permission from the image copyright owner when using works created by others. Image users can apply to image copyright holders for the right to use images or purchase copyrights through various channels. When an image user applies for a payment to use an image, after the payment is completed, the image copyright owner will authorize the specific image user to use the image through an image usage agreement. The agreement is signed by both parties, and the agreement stipulates how the licensee uses the image under what circumstances (including how to edit, to whom, etc.). However, in actual use, it is difficult to determine whether the image user is honestly following the agreement to use the image only through the agreement. It often needs to cooperate with certain technical methods, such as image forensics technologies such as digital watermarking and perceptual hashing, to identify and detect Legality of image editing. These technical methods are difficult to detect the legality of image editing behavior and user identity at the same time, and there are limitations in the detection function.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention provides an aggregation algorithm and a digital signature scheme based on cryptography, which solves the problem that the traditional image authentication method cannot verify the behavior and identity of the editing user at the same time, and solves the problem of false detection by the traditional method. Based on the aggregation algorithm Non-interactive image editing legality detection method.

The non-interactive image editing legality detection method based on the aggregation algorithm of the present invention adopts the following technical scheme: it includes the following specific steps:

S1: The image copyright owner sets security parameters, uses the group generation method to generate a bilinear group with a symmetrical structure, and then uses the hash algorithm to set public parameters;

S2: The image copyright owner calls the key generation algorithm based on the security parameters to generate the copyright owner's public key and the copyright owner's private key; the image user obtains the user's private key from the positive integer multiplication group in the bilinear group, and calculates the user's public key; The public key of the copyright owner and the public key of the user are publicly released, and the private key of the copyright owner and the private key of the user are kept privately;

S3: The image copyright owner formulates image editing rules, and combines the user's public key to generate an image editing license for the image user;

S4: The image user edits the image according to the editing license and generates additional evidence for the edited new image;

S5: After receiving the image and the new image, the verifying party verifies whether the editing of the new image is legally authorized according to the editing license and additional evidence.

Further, the step S1 includes:

S1-1: Set the safety parameter λ, λ is a constant, and use the group generation method to generate a bilinear group BP=(G ₁ ,G ₁ ,G ₂ ,e,p) with a symmetrical structure, where p is a large prime number and p> 2 ^λ , G ₁ , G ₂ are all multiplicative cyclic groups with order p, g is the generating element of group G ₁ , and e is the symmetric bilinear operation e: G ₁ ×G ₁ →G ₂ ;

S1-2: Establish hash function H ₁ : {0,1} ^* → Z _p ^* , H ₂ : {0,1} ^* → G ₁ , where {0,1} ^* is any string, Z _p ^* is the positive integer multiplication group of modulo p operation;

S1-3: Set the public parameters as param={g, H ₁ , H ₂ , BP}.

Further, in the step S2, the copyright owner public key and the copyright owner private key set by the image copyright owner based on the security parameter call signature key include:

S2-1: Select a random number x∈Z _p ^* , and select a standard signature scheme, call the key generation algorithm DSS.KeyGen(λ) of the standard signature scheme based on the security parameter λ, and generate a signature public-private key pair (sk _s ,pk _s );

S2-2: Set the private key of the copyright owner as sk _A = (x, sk _s );

获得版权人公钥为pk_A＝({X_i|0≤i≤n},pk_s)；S2-3: Calculate for all i=0 to n

Obtaining the public key of the copyright owner is pk _A = ({X _i |0≤i≤n},pk _s );

In the step S2, the image user obtains the user private key from the positive integer multiplication group in the bilinear group, and calculates the user public key including:

S2-4: Randomly select y∈Z _p ^* and set user private key sk _E =y;

S2-5: Calculate Y=g ^y and set user public key pk _E =Y.

Further, the step S3 includes:

S3-1: Establish image editing rules: set M _i =f _i (M _i ,a _i ) for all images i=0to|P|;

S3-2: Obtain the hash value h _i =H ₁ (M _i ) of the image M _i , and select a random number k∈Z _p ^* and use the image user public key pk _E to calculate the aggregation value:

S3-3: Obtain the signature σ=DSS.Sign(A,sk _s ) through the aggregation value A;

S3-4: Obtain the editing license EC=(A, k, σ).

Further, the step S4 includes:

S4-1: Generating a new image M' based on the edited image M _i edited by the editing license EC;

S4-2: Obtain the hash value h _i =H ₁ (M') of the new image M';

S4-3: Generate additional evidence:

Further, the step S4 also includes that the image user verifies whether the editing license has been tampered with before editing the image: if DSS.Verify(A,σ,pk _s )=false, stop editing and return empty, otherwise perform image editing, And generate additional evidence for new images.

Further, in the step S5, the verifying party verifies whether the new image editing behavior is legally authorized according to the editing license certificate and additional evidence, including:

S5-1: Perform signature verification to prevent the editing license EC from being tampered with: if DSS.Verify(A,σ,pk _s )=false, the verification fails, otherwise proceed to the next step;

S5-2: Verify the correctness of additional evidence:

则新图像编辑行为是经过合法授权，like

Then the new image editing behavior is legally authorized,

Otherwise, the new image editing behavior is not legally authorized, which infringes the legal rights of the image copyright owner.

Compared with the prior art, the present invention has the beneficial effect: on the basis of public key cryptography, the present invention optimizes the aggregator in cryptography, and redesigns the proof of membership in the traditional aggregator from publicly computable to only The designated user can be calculated, and the design of a new cryptographic component——Accountable Accumulators (AACC, Accountable Accumulators) is realized, and the new component is combined with digital signature technology to realize the legality detection of image editing in a non-interactive environment. In the image authentication, the editing behavior detection and the identity verification of the editor are realized at the same time, which not only ensures the security of the image application, but also has efficient and convenient operation, which is conducive to the image receiver to quickly verify whether the received image involves infringement, and to effectively protect image knowledge. Property rights provide key technical support.

Description of drawings

The accompanying drawings described here are used to provide a further understanding of the application, in the accompanying drawings:

Fig. 1 is a system architecture diagram of the present invention;

Fig. 2 is a work flow chart of the present invention;

Fig. 3 is a working block diagram of the present invention;

Fig. 4 is a comparison chart of algorithm running time under the 80-bit security level of the present invention.

Detailed ways

Referring to shown in Fig. 1, embodiment is based on the non-interactive image editing legitimacy detection method of aggregation algorithm, adopts following technical scheme: it comprises the following specific steps:

S1: The image copyright owner sets security parameters, uses the group generation method to generate a bilinear group with a symmetrical structure, and then uses the hash algorithm to set public parameters;

S2: The image copyright owner calls the key generation algorithm based on the security parameters to generate the copyright owner's public key and the copyright owner's private key; the image user obtains the user's private key from the positive integer multiplication group in the bilinear group, and calculates the user's public key; The public key of the copyright owner and the public key of the user are publicly released, and the private key of the copyright owner and the private key of the user are kept privately;

S3: The image copyright owner formulates image editing rules, and combines the user's public key to generate an image editing license for the image user;

S4: The image user edits the image according to the editing license and generates additional evidence for the edited new image;

S5: After receiving the image and the new image, the verifying party verifies whether the editing of the new image is legally authorized according to the editing license and additional evidence.

Further, the step S1 includes:

S1-1: Set the safety parameter λ, λ is a constant, and use the group generation method to generate a bilinear group BP=(G ₁ ,G ₁ ,G ₂ ,e,p) with a symmetrical structure, where p is a large prime number and p> 2 ^λ , G ₁ , G ₂ are all multiplicative cyclic groups with order p, g is the generating element of group G ₁ , and e is the symmetric bilinear operation e: G ₁ ×G ₁ →G ₂ ;

S1-2: Establish hash function H ₁ : {0,1} ^* → Z _p ^* , H ₂ : {0,1} ^* → G ₁ , where {0,1} ^* is any string, Z _p ^* is the positive integer multiplication group of modulo p operation;

S1-3: Set the public parameters as param={g, H ₁ , H ₂ , BP}.

Further, in the step S2, the copyright owner public key and the copyright owner private key set by the image copyright owner based on the security parameter call signature key include:

S2-1: Select a random number x∈Z _p ^* , and select a standard signature scheme, call the key generation algorithm DSS.KeyGen(λ) of the standard signature scheme based on the security parameter λ, and generate a signature public-private key pair (sk _s ,pk _s );

S2-2: Set the private key of the copyright owner as sk _A = (x, sk _s );

获得版权人公钥为pk_A＝({X_i|0≤i≤n},pk_s)；S2-3: Calculate for all i=0 to n

Obtaining the public key of the copyright owner is pk _A = ({X _i |0≤i≤n},pk _s );

In the step S2, the image user obtains the user private key from the positive integer multiplication group in the bilinear group, and calculates the user public key including:

S2-4: Randomly select y∈Z _p ^* and set user private key sk _E =y;

S2-5: Calculate Y=g ^y and set user public key pk _E =Y.

Further, the step S3 includes:

S3-1: Establish image editing rules: set M _i =f _i (M _i ,a _i ) for all images i=0to|P|;

S3-2: Obtain the hash value h _i =H ₁ (M _i ) of the image M _i , and select a random number k∈Z _p ^* and use the image user public key pk _E to calculate the aggregation value:

S3-3: Obtain the signature σ=DSS.Sign(A,sk _s ) through the aggregation value A;

S3-4: Obtain the editing license EC=(A, k, σ).

Further, the step S4 includes:

S4-1: Generating a new image M' based on the edited image M _i edited by the editing license EC;

S4-2: Obtain the hash value h _i =H ₁ (M') of the new image M';

S4-3: Generate additional evidence:

Further, the step S4 also includes that the image user verifies whether the editing license has been tampered with before editing the image: if DSS.Verify(A,σ,pk _s )=false, stop editing and return empty, otherwise perform image editing, And generate additional evidence for new images.

Further, in the step S5, the verifying party verifies whether the new image editing behavior is legally authorized according to the editing license certificate and additional evidence, including:

S5-1: Perform signature verification to prevent the editing license EC from being tampered with: if DSS.Verify(A,σ,pk _s )=false, the verification fails, otherwise proceed to the next step;

S5-2: Verify the correctness of additional evidence:

则新图像编辑行为是经过合法授权，like

Then the new image editing behavior is legally authorized,

Otherwise, the new image editing behavior is not legally authorized, which infringes the legal rights of the image copyright owner.

The running efficiency of the algorithm is tested in detail by computer. The experimental equipment is an ordinary Lenovo laptop (model: ThinkPad X390), equipped with a 3.4GHz Intel i5-7500 dual-core central processing unit (CPU), and equipped with 8G memory (RAM). The program coding is completed by C++ language combined with GNU Multiple Precision Arithmetic (GMP) Library and Pairing-Based Cryptography (PBC) Library. The program code is compiled by Visual Studio 2017 and run on the Win10 operating system. The scheme selects the symmetric curve Curve A in PBC for testing, and the digital signature scheme selects the short signature BLS scheme based on bilinear mapping.

The experimental image selects the image Lenna (resolution 256*256), and uses Photoshop to edit the original image into 400 new images. The editing methods include common sharpening, denoising, compression, etc. The experiment selects n=100～400 for testing, the growth granularity is 100, and there are 4 groups of test data;

First, generate the public and private keys needed for the operation of each entity according to S1 and S2;

Secondly, according to S3, the image is preprocessed and a hash operation is performed to generate an image hash set. The method of hashing the image is: read the image in binary form, and then use the hash function in PBC to map the bit stream of the image into elements on the group G ₁ . Compared with other sub-algorithms, this method is more efficient for image hashing, and will not hinder the efficiency of the scheme. Then the hash set is aggregated to generate the editing license EC.

Then, edit the image according to S4 and generate additional evidence SP of the image;

Finally, the edited image is verified according to the editing license EC and the additional evidence SP as described in S5.

Please refer to Figure 3 and Table 1, the time consumption of the key generation algorithm is the largest at the 80-bit security level and increases linearly with the increase of the number of edits n, but since the key generation algorithm only needs to be run once in an authorization operation , has limited impact on system efficiency, while the verification algorithm is constant time independent of the number of authorized edits of the image.

Number of edits Image Hash (ms) key generation (ms) Authorization (ms) Edit proof (ms) verify(ms) 100 26 380 79 33 34 200 66 893 115 56 33 300 88 1178 143 96 36 400 150 1630 201 150 35

Table 1 The running time of each sub-algorithm of the scheme under the 80-bit security level

Although the embodiments of the present invention have been shown and described, those skilled in the art can understand that various changes, modifications and substitutions can be made to these embodiments without departing from the principle and spirit of the present invention. and modifications, the scope of the invention is defined by the appended claims and their equivalents.

Claims (2)

1. The non-interactive image editing legality detection method based on aggregation algorithm, is characterized in that: it comprises the following specific steps: S1: The image copyright owner sets security parameters, uses the group generation method to generate a bilinear group with a symmetrical structure, and then uses the hash algorithm to set public parameters; Step S1 includes: S1-1: Set the safety parameter λ, λ is a constant, and use the group generation method to generate a bilinear group BP=(G ₁ ,G ₁ ,G ₂ ,e,p) with a symmetrical structure, where p is a large prime number and p> 2 ^λ , G ₁ , G ₂ are all multiplicative cyclic groups with order p, g is the generating element of group G ₁ , and e is the symmetric bilinear operation e: G ₁ ×G ₁ →G ₂ ; S1-2: Establish hash function H ₁ : {0,1} ^* → Z _p ^* , H ₂ : {0,1} ^* → G ₁ , where {0,1} ^* is any string, Z _p ^* is the positive integer multiplication group of modulo p operation; S1-3: Set public parameters as param={g, H ₁ , H ₂ , BP}; S2: The image copyright owner calls the key generation algorithm based on the security parameters to generate the copyright owner's public key and the copyright owner's private key; the image user obtains the user's private key from the positive integer multiplication group in the bilinear group, and calculates the user's public key; The public key of the copyright owner and the public key of the user are publicly released, and the private key of the copyright owner and the private key of the user are kept privately; In step S2, the copyright owner's public key and copyright owner's private key set by the image copyright owner based on the security parameter call signature key include: S2-1: Select a random number x∈Z _p ^* , and select a standard signature scheme, call the key generation algorithm DSS.KeyGen(λ) of the standard signature scheme based on the security parameter λ, and generate a signature public-private key pair (sk _s ,pk _s ); S2-2: Set the private key of the copyright owner as sk _A = (x, sk _s ); S2-3: Calculate for all i=0 to n Obtaining the public key of the copyright owner is pk _A = ({X _i |0≤i≤n},pk _s ); In the step S2, the image user obtains the user private key from the positive integer multiplication group in the bilinear group, and calculates the user public key including: S2-4: Randomly select y∈Z _p ^* and set user private key sk _E =y; S2-5: Calculate Y=g ^y and set user public key pk _E =Y; S3: The image copyright owner formulates image editing rules, and combines the user public key to generate an image editing license for the image user; step S3 includes: S3-1: Establish image editing rules: set M _i =f _i (M _i ,a _i ) for all images with i=0 to |P|; S3-2: Obtain the hash value h _i =H ₁ (M _i ) of the image M _i , and select a random number k∈Z _p ^* and use the image user public key pk _E to calculate the aggregation value: S3-3: Obtain the signature σ=DSS.Sign(A,sk _s ) through the aggregation value A; S3-4: Obtain the editing license EC=(A,k,σ); S4: The image user edits the image according to the editing license and generates additional evidence for the edited new image; step S4 includes: S4-1: Generating a new image M' based on the edited image M _i edited by the editing license EC; S4-2: Obtain the hash value h _i =H ₁ (M') of the new image M'; S4-3: Generate additional evidence: S5: After the verification party receives the new image, it verifies whether the new image editing behavior is legally authorized according to the editing license and additional evidence; in step S5, the verification party verifies whether the new image editing behavior is legally authorized according to the editing license and additional evidence, including: S5-1: Perform signature verification to prevent the editing license EC from being tampered with: if DSS.Verify(A,σ,pk _s )=false, the verification fails, otherwise proceed to the next step; S5-2: Verify the correctness of additional evidence: like Then the new image editing behavior is legally authorized, Otherwise, the new image editing behavior is not legally authorized, which infringes the legal rights of the image copyright owner. 2. The non-interactive image editing legality detection method based on aggregation algorithm according to claim 1, characterized in that: the step S4 also includes the image user verifying whether the editing license has been tampered with before editing the image: if the DSS .Verify(A,σ,pk _s )=false, stop editing and return null, otherwise image editing is performed and additional evidence is generated for the new image.

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