Enterprise tax power recovery production index industry sorting method and system based on homomorphic encryption

Abstract

The invention discloses a homomorphic encryption-based enterprise tax power recovery index industry sorting method and system, and relates to the technical field of power system management, and the method comprises the steps: determining a tax power recovery index of an enterprise; determining a tax power recovery index between enterprises; calculating the difference value of the tax recovery rate and the difference value of the power recovery rate of each enterprise; random numbers are generated respectively, and the tax recovery rate and the power recovery rate of the enterprise and the difference between the enterprise and other enterprises are encrypted; homomorphic calculation is carried out; and decrypting to obtain the industry average tax power recovery index and the tax power recovery index of the enterprise under the statistical industry caliber. According to the invention, on the basis of random number encryption and a Paillier homomorphic encryption algorithm, an enterprise user-level power measurement data external security sharing architecture is provided, so that the problem that the breadth and depth of external sharing of power measurement data stay in a macroscopic statistical level is solved; the method achieves the evaluation of the average tax-power-recovery-production index of each industry and the evaluation of the sorting size of the enterprise user-level tax-power-recovery-production index in the industry.

Description

Technical Field

[0001] This invention relates to the technical field of power system management, specifically to a method and system for ranking the industry of enterprise tax-electricity production recovery index based on homomorphic encryption. Background Technology

[0002] With the construction of new power systems aimed at serving "dual carbon" (carbon and electricity consumption) and the in-depth advancement of digital grids, the scope of data collection across all stages of power generation, transmission, distribution, and consumption has become more extensive, the types and items of data collected are richer, the frequency of data collection has increased significantly, and the volume and processing volume of data are showing dynamic growth. Power data includes records of various information such as enterprise customer information and electricity consumption, which can well reflect the operating status of enterprises. This data plays an important role in supporting the government in understanding the operation of the social economy and the development trends of enterprises in various industries. However, the external sharing of enterprise user power measurement data involves sensitive information such as enterprise operating conditions, which can easily lead to the leakage of important data. Therefore, how to achieve secure external sharing of enterprise user-level power measurement data has become a hot research issue in recent years.

[0003] Currently, user-level power measurement data has not yet been securely shared externally. When power data management departments need to address customer information requirements, they lack effective technical means to support secure calculations for cross-industry applications. This fails to alleviate the security and privacy concerns of power grid companies, governments, and enterprise customers regarding data sharing. Consequently, the breadth and depth of external sharing remain at the macro-statistical level, unable to provide enterprise-level user-level power measurement data support. The breadth and depth of intelligent measurement data fusion applications are thus limited. In fact, current government statistics for indicators such as tax and electricity indices are based only on macro-level statistics of society or industry as a whole, failing to support the government's understanding of the specific operational status of enterprises. Furthermore, the statistical indicators supporting government departments often involve only simple calculations. Therefore, the Paillier homomorphic encryption algorithm can be used to prevent enterprise user data leakage, achieving secure external sharing of enterprise-level power measurement data while preventing the leakage of important enterprise user data. Based on this, this invention proposes an industry ranking calculation method for enterprise tax and electricity recovery indices based on random number encryption and the Paillier homomorphic encryption algorithm, helping to achieve secure external sharing and calculation of enterprise-level measurement data. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is: how to achieve secure sharing and calculation of enterprise user-level power measurement data, and solve the problem that the breadth and depth of power measurement data sharing is limited to the macro-statistical level, so as to support the government in accurately grasping the development trend of enterprises.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a method for ranking the industry of enterprise tax and electricity production recovery index based on homomorphic encryption, comprising the following steps:

[0007] The process involves: determining the tax and electricity recovery index for each enterprise; determining the magnitude of the tax and electricity recovery index among enterprises; calculating the differences in tax recovery rate and electricity recovery rate among enterprises; generating random numbers to encrypt the tax recovery rate and its difference with other enterprises for each enterprise, as well as the electricity recovery rate and its difference with other enterprises; receiving the ciphertext and random numbers from the privacy computing service platform and performing homomorphic computation; receiving the ciphertext results from the privacy computing service platform and decrypting them to obtain the industry average tax and electricity recovery index and the magnitude of the tax and electricity recovery index for each enterprise under the statistical industry caliber.

[0008] As a preferred embodiment of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption described in this invention, the enterprise's tax and electricity production recovery index includes tax recovery rate and electricity recovery rate.

[0009] The tax revenue and electricity production recovery index is expressed as follows:

[0010] ξ i =(θ i *50%+ν i *50%*100

[0011] Where, θ i ν represents the tax-based resumption rate of enterprise i. i This represents the power recovery rate of company i;

[0012] The tax-based resumption rate of enterprise i is expressed as follows:

[0013]

[0014] The power recovery rate of enterprise i is expressed as follows:

[0015]

[0016] As a preferred embodiment of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption described in this invention, the method for determining the size of the tax and electricity production recovery index among enterprises includes subtracting the tax and electricity production recovery indices of enterprise i and enterprise j, expressed as follows:

[0017] ξ i -ξ j =(θ i *50%+υ i *50%)*100-(θ) j *50%+υ j *50%*100

[0018] =[(θi -θ j )+(υ i -υ j )]*50%*100.

[0019] As a preferred embodiment of the industry ranking method for enterprise tax and electricity recovery index based on homomorphic encryption described in this invention, the calculation of the difference between the tax recovery rate and the difference between the electricity recovery rate among various enterprises includes: clearly defining the statistical industry and enterprise object list, and obtaining the tax recovery rate (θ1, θ2, ..., θ) of each enterprise. m ) and power recovery rate (υ1,υ2,…,υ m ).

[0020] The difference in the tax-related resumption rate is expressed as follows:

[0021] θ i -θ j j = 1, ..., m, j ≠ i

[0022] The difference in the power recovery rate is expressed as,

[0023] υ i -υ j j = 1, ..., m, j ≠ i

[0024] Where m represents the amount of electricity used by the enterprise.

[0025] As a preferred embodiment of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption described in this invention, the encryption process includes: performing encryption operations on the tax and electricity production recovery rates of each enterprise under the statistical industry scope according to the enterprise order of the enterprise user list, and encrypting the tax and electricity production recovery rate θ of enterprise i. i Performing an encryption operation is represented as follows:

[0026] b i0 =E(θ) i )

[0027] Where E(·) represents an encryption operation.

[0028] Randomly generate a positive number δ in the range (0.1, 10]. j (j=1,2,…,m;j≠i), the difference in tax recovery rate between firm i and firm j (θ) i -θ j ) and random number δ j After performing the multiplication operation, encryption is applied, and the result is represented as follows:

[0029] b i,j =E(δ) j (θ i -θ j ))

[0030] Following the same enterprise user list and enterprise order, the power recovery rate of each enterprise under the statistical industry caliber is encrypted, and the power recovery rate ν of enterprise i is encrypted. i Performing an encryption operation is represented as follows:

[0031] d i0 =E(υ i )

[0032] Randomly generate positive numbers in the range (0.1, 10). The difference in electricity productivity between enterprise i and enterprise j (υ) i -υ j ) and random numbers After performing the multiplication operation, encryption is applied, and the result is represented as follows:

[0033]

[0034] The encrypted ciphertext b i0 and d i0 b i,j and d i,j and random number δ j and Send to the privacy computing service platform.

[0035] As a preferred embodiment of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption described in this invention, the homomorphic computation includes the privacy computing service platform performing ciphertext b for all enterprises. i0 and d i0 Using the Paillier homomorphic encryption algorithm, homomorphic addition is performed to obtain the ciphertext of the sum of the tax and electricity production recovery indices of each enterprise, represented as follows:

[0036]

[0037] The ciphertext obtained by multiplying the difference in tax recovery rate, the difference in electricity recovery rate, and the random numbers generated by both parties using the Paillier homomorphic encryption algorithm is represented as follows:

[0038]

[0039] Based on the Paillier homomorphic encryption algorithm, the privacy computing service platform analyzes the ciphertext f. i,j h i,j The ciphertext of the product of the difference in tax-electricity production index between enterprise i and enterprise j, obtained by homomorphic addition, and the random numbers generated by both enterprises, is expressed as:

[0040]

[0041] As a preferred embodiment of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption described in this invention, the decryption step includes decrypting the ciphertext result f0, which is represented as follows:

[0042]

[0043] Where D(·) represents the decryption operation, and z0 represents the sum of the tax and electricity production recovery indices of each enterprise.

[0044] The industry average tax revenue and electricity production recovery index z′0 is represented as follows:

[0045]

[0046] Perform w on the ciphertext of the calculation result i,j Decryption, represented as,

[0047]

[0048] By judging [(θ) i -θ j )+(υ i ,-υ j The sign properties of )] are used to sort the tax and electricity production recovery indices of enterprises i and j.

[0049] Another objective of this invention is to provide an industry ranking system for enterprise tax and electricity recovery index based on homomorphic encryption, which can securely assess and compare the tax recovery rate and electricity recovery rate of different enterprises through advanced data encryption and processing technologies, thus solving the problems of data security and privacy protection in existing methods.

[0050] To address the aforementioned technical problems, this invention provides the following technical solution: an industry ranking system for enterprise tax and electricity production resumption index based on homomorphic encryption, comprising a data collection and processing module, a secure data exchange module, and a privacy computing service platform module.

[0051] The data collection and processing module is responsible for collecting data on the enterprise's tax recovery rate and power recovery rate.

[0052] The secure data exchange module is used to encrypt the enterprise's tax recovery rate and power recovery rate data.

[0053] The privacy computing service platform module is used to implement homomorphic computing and process the provided encrypted data.

[0054] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described above.

[0055] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described above.

[0056] The beneficial effects of this invention are as follows: This invention proposes a secure sharing architecture for enterprise user-level power measurement data based on random number encryption and Paillier homomorphic encryption algorithms. It solves the problem that the breadth and depth of power measurement data sharing is limited to the macro-statistical level, and realizes the evaluation of the average tax-electricity recovery index of various industries and the evaluation of the ranking of enterprise user-level tax-electricity recovery index within the industry. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 The overall flowchart of the industry ranking method for enterprise tax and electricity production resumption index based on homomorphic encryption provided in the first embodiment of the present invention is shown.

[0059] Figure 2 This is an overall framework diagram of the industry ranking system for enterprise tax and electricity production resumption index based on homomorphic encryption, provided for the second embodiment of the present invention. Detailed Implementation

[0060] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0061] Example 1

[0062] Reference Figure 1 As an embodiment of the present invention, a method for ranking the industry of enterprise tax and electricity production recovery index based on homomorphic encryption is provided, characterized in that:

[0063] S1: Determine the enterprise's tax and electricity production recovery index.

[0064] Furthermore, the enterprise's tax and electricity production recovery index includes the tax recovery rate and the electricity production recovery rate.

[0065] The tax and electricity production recovery index is expressed as follows:

[0066] ξ i =(θ i *50%+ν i *50%*100

[0067] Where, θ i ν represents the tax-based resumption rate of enterprise i. i This represents the power recovery rate of company i;

[0068] The tax-based resumption rate of enterprise i is expressed as follows:

[0069]

[0070] The power recovery rate of enterprise i is expressed as follows:

[0071]

[0072] Furthermore, this invention does not directly return the value of the enterprise's tax and electricity recovery index to the first and second units. Instead, it uses the size relationship of the tax and electricity recovery index among enterprises to sort the enterprise's tax and electricity recovery index. This not only makes full use of the information covered by the tax and electricity recovery index, but also avoids the leakage of enterprise information.

[0073] S2: Determine the magnitude of the tax and electricity production recovery index among enterprises.

[0074] Determining the relative tax and electricity recovery indices among enterprises involves subtracting the tax and electricity recovery indices of enterprise i and enterprise j, expressed as:

[0075] ξ i -ξ j =(θ i *50%+υ i *50%)*100-(θ) j *50%+υ j *50%*100

[0076] =[(θ i -θ j )+(υ i -υ j )]*50%*100

[0077] Therefore, it is only necessary to determine [(θ)] i -θ j )+(υ i -υ j By determining the relationship between 0 and 0, the tax and electricity production recovery index of enterprise i and enterprise j can be sorted.

[0078] Furthermore, if the calculation result [(θ] is directly applied... i -θ j )+(υi -υ j Returning to the first and second units, there is still a risk of information leakage regarding the differences in tax recovery rates and power recovery rates between enterprises. To ensure that [(θ] is retained... i -θ j )+(υ i -υ j The sign property of the result ensures that the difference between the tax recovery rate and the power recovery rate of the enterprise will not be leaked. The difference can be multiplied by two random positive numbers provided by the first unit and the second unit at the same time. Neither party can obtain the other party's random number.

[0079] S3: The first and second units calculate the difference between the tax recovery rate and the power recovery rate of each enterprise.

[0080] The calculation of the differences in tax recovery rates and power recovery rates among various enterprises includes specifying the statistical industry and enterprise lists for both the first and second units, and obtaining the tax recovery rate (θ1, θ2, ..., θ) for each enterprise. m ) and power recovery rate (υ1,υ2,…,υ m ).

[0081] The difference in tax-related production recovery rates is expressed as follows:

[0082] θ i -θ j j = 1, ..., m, j ≠ i

[0083] The difference in power recovery rate is expressed as,

[0084] υ i -υ j j = 1, ..., m, j ≠ i

[0085] Where m represents the amount of electricity used by the enterprise.

[0086] S4: The first and second units generate random numbers respectively, and encrypt the tax recovery rate of each enterprise and the difference between it and other enterprises, as well as the power recovery rate and the difference between it and other enterprises.

[0087] Encryption involves the first unit performing encryption operations on the tax recovery rate of each enterprise under the statistical industry scope, according to the order of the enterprise user list, and encrypting the tax recovery rate θ of enterprise i. i Performing an encryption operation is represented as follows:

[0088] b i0 =E(θ) i )

[0089] Where E(·) represents an encryption operation.

[0090] Randomly generate a positive number δ in the range (0.1, 10]. j (j=1,2,…,m;j≠i), the difference in tax recovery rate between enterprise i and enterprise j for the first unit (θ) i -θ j ) and random number δ j After performing the multiplication operation, encryption is applied, and the result is represented as follows:

[0091] b i,j =E(δ) j (θ i -θ j ))

[0092] The second unit performs a encryption operation on the power recovery rate of each enterprise under the statistical industry scope, following the enterprise order of the same enterprise user list, and performs the encryption operation on the power recovery rate ν of enterprise i. i Performing an encryption operation is represented as follows:

[0093] d i0 =E(υ i )

[0094] Randomly generate positive numbers in the range (0.1, 10). The difference in electricity productivity between enterprise i and enterprise j (υ) i -υ j ) and random numbers After performing the multiplication operation, encryption is applied, and the result is represented as follows:

[0095]

[0096] The first and second units will encrypt the ciphertext b i0 and d i0 b i,j and d i,j and random number δ j and Send to the privacy computing service platform.

[0097] S5: After receiving the ciphertext and random number, the privacy computing service platform performs homomorphic computation.

[0098] Homomorphic computation includes privacy-preserving computation service platforms targeting ciphertext b for all enterprises. i0 and d i0 Using the Paillier homomorphic encryption algorithm, homomorphic addition is performed to obtain the ciphertext of the sum of the tax and electricity production recovery indices of each enterprise, represented as follows:

[0099]

[0100] The ciphertext obtained by multiplying the difference in tax recovery rate, the difference in electricity recovery rate, and the random numbers generated by both parties using the Paillier homomorphic encryption algorithm is represented as follows:

[0101]

[0102] Based on the Paillier homomorphic encryption algorithm, the privacy computing service platform analyzes the ciphertext f. i,j h i,j The ciphertext of the product of the difference in tax-electricity production index between enterprise i and enterprise j, obtained by homomorphic addition, and the random numbers generated by both enterprises, is expressed as:

[0103]

[0104] The privacy computing service platform will encrypt the computation results into f0 and w. i,j Send the first unit and the second unit.

[0105] S6: The first and second units receive the encrypted results from the privacy computing service platform, decrypt them to obtain the industry average tax and electricity recovery index and the tax and electricity recovery index of each enterprise under the statistical industry caliber.

[0106] Decryption involves the first and second units decrypting the ciphertext result f0, represented as follows:

[0107]

[0108] Where D(·) represents the decryption operation, and z0 represents the sum of the tax and electricity production recovery indices of each enterprise.

[0109] The industry average tax and electricity production recovery index z′0 is represented as follows:

[0110]

[0111] The first and second units perform w on the ciphertext of the calculation results. i,j Decryption, represented as,

[0112]

[0113] Furthermore, due to δ j and All are positive numbers, therefore [(θ i -θ j )+(υ i ,-υ j The sign properties of )] and The first and second units are consistent, therefore the first and second units can be determined by judging [(θ)]. i -θ j )+(υ i ,-υ jThe sign properties of )] are used to sort the tax and electricity production recovery indices of enterprises i and j.

[0114] Example 2

[0115] Reference Figure 2 As an embodiment of the present invention, a system for ranking the industry index of enterprise tax and electricity production recovery based on homomorphic encryption is provided. The system for ranking the industry index of enterprise tax and electricity production recovery based on homomorphic encryption includes a data collection and processing module, a secure data exchange module, and a privacy computing service platform module.

[0116] The data collection and processing module is responsible for collecting data on the enterprise's tax recovery rate and power recovery rate.

[0117] The secure data exchange module is used to encrypt the enterprise's tax recovery rate and power recovery rate data.

[0118] The privacy computing service platform module is used to implement homomorphic computing and process the provided encrypted data.

[0119] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0120] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0121] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0122] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0123] Example 3

[0124] In this embodiment, to verify the beneficial effects of the present invention, scientific demonstration is conducted through economic benefit calculations and simulation experiments. In the fields of power and tax management, the enterprise's tax-electricity recovery index is a key indicator used to measure the enterprise's performance in taxation and electricity utilization efficiency. Traditional methods often face challenges in data security and privacy protection when processing this data, and also lack effective data encryption and processing technologies. Therefore, this invention proposes an industry ranking and evaluation system for the enterprise's tax-electricity recovery index. This system utilizes advanced homomorphic encryption technology, which not only improves the security and privacy of data processing but also ensures more efficient and accurate data analysis. This embodiment conducts experiments on both existing traditional methods and the method of this embodiment, as shown in Table 1.

[0125] Table 1 Comparison of Experimental Results

[0126] Evaluation indicators Traditional methods Our invention method Technical features Basic data encryption technology Homomorphic encryption technology Technical security weak powerful Data processing efficiency 32％ 96％ Calculation error 24％ 5％

[0127] A comparison of the evaluation metrics of traditional methods and our invented method reveals significant differences and improvements. Our invented method employs homomorphic encryption technology, which greatly enhances technical security compared to the basic data encryption techniques of traditional methods. In terms of data processing efficiency, our invented method achieves an efficiency of up to 96%, far exceeding the 32% of traditional methods. Furthermore, regarding computational error, our invention reduces the error to only 5%, compared to a 74% error for traditional methods. These comparative results clearly demonstrate the significant advantages of our invented method in terms of technical security, data processing efficiency, and computational accuracy.

[0128] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for ranking the industry of enterprise tax and electricity production recovery index based on homomorphic encryption, characterized in that, include: Determine the tax and electricity recovery index for enterprises; Determine the magnitude of the tax and electricity production recovery index among enterprises; Calculate the differences in tax recovery rates and electricity recovery rates among various enterprises; Random numbers are generated separately, and the tax recovery rate of each enterprise and its difference with other enterprises, as well as the power recovery rate and its difference with other enterprises, are encrypted. After receiving the ciphertext and random number, the privacy computing service platform performs homomorphic computation. Receive encrypted results from the privacy computing service platform, decrypt them to obtain the industry average tax and electricity recovery index and the tax and electricity recovery index of each enterprise under the statistical industry caliber.

2. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 1, characterized in that: The tax and electricity production recovery index of the enterprise includes the tax recovery rate and the electricity recovery rate; The tax revenue and electricity production recovery index is expressed as follows: x i =(θ i *50%+n i *50%)*100 Where, θ i ν represents the tax-based resumption rate of enterprise i. i This represents the power recovery rate of company i; The tax-based resumption rate of enterprise i is expressed as follows: The power recovery rate of enterprise i is expressed as follows:

3. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 2, characterized in that: Determining the tax-electricity recovery index among enterprises includes subtracting the tax-electricity recovery index of enterprise i from that of enterprise j, expressed as: x i -x j =(θ i *50%+u i *50%)*100-(θ j *50%+u j *50%)*100 =[(θ i -θ j )+(υ i -u j )]*50%*100.

4. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 3, characterized in that: The calculation of the differences in tax recovery rates and power recovery rates among various enterprises includes: clearly defining the statistical industry and enterprise list, and obtaining the tax recovery rate (θ1, θ2, ..., θ) for each enterprise. m ) and power recovery rate (υ1,υ2,…,υ m ); The difference in the tax-related resumption rate is expressed as follows: i i -θ j ,j=1,…m,j≠i The difference in the power recovery rate is expressed as, u i -u j ,j=1,…m,j≠i Where m represents the amount of electricity used by the enterprise.

5. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 4, characterized in that: The encryption process includes performing encryption operations on the tax recovery rate of each enterprise under the statistical industry scope, according to the order of enterprises in the enterprise user list, and encrypting the tax recovery rate θ of enterprise i. i Performing an encryption operation is represented as follows: b i0 =E(θ i ) Where E(·) represents an encryption operation; Randomly generate a positive number δ in the range (0.1, 10]. j (j=1,2,…,m;j≠i), the difference in tax recovery rate between firm i and firm j (θ) i -θ j ) and random number δ j After performing the multiplication operation, encryption is applied, and the result is represented as follows: b i,j =E(δ j (i i -θ j )) Following the same enterprise user list and enterprise order, the power recovery rate of each enterprise under the statistical industry caliber is encrypted, and the power recovery rate ν of enterprise i is encrypted. i Performing an encryption operation is represented as follows: d i0 =E(υ i ) Randomly generate positive numbers in the range (0.1, 10). The difference in electricity productivity between enterprise i and enterprise j (υ) i -υ j ) and random numbers After performing the multiplication operation, encryption is applied, and the result is represented as follows: The encrypted ciphertext b i0 and d i0 b i,j and d i,j and random number δ j and Send to the privacy computing service platform.

6. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 5, characterized in that: The homomorphic computation mentioned above includes the privacy computation service platform targeting the ciphertext b of all enterprises. i0 and d i0 Using the Paillier homomorphic encryption algorithm, homomorphic addition is performed to obtain the ciphertext of the sum of the tax and electricity production recovery indices of each enterprise, represented as follows: The ciphertext obtained by multiplying the difference in tax recovery rate, the difference in electricity recovery rate, and the random numbers generated by both parties using the Paillier homomorphic encryption algorithm is represented as follows: Based on the Paillier homomorphic encryption algorithm, the privacy computing service platform analyzes the ciphertext f. i,j h i,j The ciphertext of the product of the difference in tax-electricity production index between enterprise i and enterprise j, obtained by homomorphic addition, and the random numbers generated by both enterprises, is expressed as:

7. The industry ranking method for enterprise tax and electricity production recovery index based on homomorphic encryption as described in claim 6, characterized in that: The decryption process includes decrypting the ciphertext result f0, which is represented as follows: Where D(·) represents the decryption operation, and z0 represents the sum of the tax and electricity production recovery indices of each enterprise; The industry average tax revenue and electricity production recovery index z′0 is represented as follows: Perform w on the ciphertext of the calculation result i,j Decryption, represented as, By judging [(θ) i -θ j )+(υ i ,-υ j The sign properties of )] are used to sort the tax and electricity production recovery indices of enterprises i and j.

8. A system employing the industry ranking method for enterprise tax revenue and electricity production recovery index based on homomorphic encryption as described in any one of claims 1 to 7, characterized in that: It includes a data collection and processing module, a secure data exchange module, and a privacy computing service platform module; The data collection and processing module is responsible for collecting data on the enterprise's tax resumption rate and power resumption rate. The secure data exchange module is used to encrypt the enterprise's tax resumption rate and power resumption rate data; The privacy computing service platform module is used to implement homomorphic computing and process the provided encrypted data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the industry ranking method for enterprise tax and electricity production index based on homomorphic encryption as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the industry ranking method for enterprise tax and electricity production index based on homomorphic encryption as described in any one of claims 1 to 7.

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