CN116933299A - Tax electric data safety fusion method, tax electric node, equipment and medium - Google Patents

Abstract

The invention relates to the field of information security technology and discloses a tax and electricity data security fusion method, tax and electricity nodes, equipment and media. The method includes: calculating a tax and electricity data fusion index by combining tax data and electricity data; receiving a security inquiry center according to a threshold The secret sharing algorithm splits the key fragments obtained by splitting the order-preserving key; jointly encrypts the tax and electricity data fusion index according to the key fragments to obtain the tax and electricity ciphertext; based on the received query interval, extracts the tax and electricity ciphertext from the key fragments. The electronic ciphertext is queried to obtain the ciphertext data set located in the query interval; the ciphertext data set is jointly decrypted according to the key fragmentation to obtain the query result. The present invention can ensure the security of keys and data by performing encryption and decryption with order-preserving keys based on the threshold secret sharing algorithm.

Description

A tax and electricity data security integration method, tax and electricity nodes, equipment and media

Technical field

The invention relates to the field of information security technology, and specifically relates to a tax and electricity data security fusion method, tax and electricity nodes, equipment and media.

Background technique

With the development of big data, data has become a new factor of production. In recent years, relevant guidance requires continuous strengthening of the in-depth application of big data technology in economic operation analysis and social management and other fields, and the construction of an agile, efficient and reusable new generation of digital technology. Technical infrastructure.

Both the tax department and the power grid company have rich data resources such as platforms, users, data, and brands. The tax and power data are huge in scale and of various types. They are comprehensive, high-frequency, real-time, and accurate, and the data of both parties have been centrally managed. The standards are unified and easy to collect. Taxation and electricity data are very complementary. The two are highly consistent in industry classification and national economic statistical standards, and have a good data fusion foundation. Therefore, tax and electricity data fusion indicators are constructed through the fusion analysis of taxation and electricity data. , which is of great significance in the precise implementation of policies by service departments and the improvement of quality and efficiency of enterprises.

Order-preserving encryption is a ciphertext query encryption method, and the ciphertext size relationship reflects the plaintext size relationship. In practical applications, the data owner needs to send the key to the data user, and decrypt the retrieved ciphertext set to obtain statistical results. However, data users may be malicious, and currently order-preserving encryption cannot be applied to multi-user scenarios. Therefore, it is necessary to realize the confidentiality requirements of the data of all parties under the energy architecture, and ensure the security of the key while realizing ciphertext query.

Contents of the invention

In view of this, the present invention provides a tax and electricity data secure fusion method, tax and electricity nodes, equipment and media to solve the problem that order-preserving encryption in the existing solution cannot ensure key security when performing data fusion and query in a multi-user scenario. technical issues.

In a first aspect, the present invention provides a tax and electricity data secure fusion method, which is applied to a tax and electricity node in a tax and electricity system. The tax and electricity system includes multiple tax and electricity nodes. The tax and electricity data secure fusion method includes: combining The tax data and electricity data calculate tax and electricity data fusion indicators; receive the key fragments obtained by splitting the order-preserving key according to the threshold secret sharing algorithm by the security query center; and perform the tax and electricity data fusion indicators according to the key fragments. joint encryption to obtain the tax and electricity ciphertext; based on the received query interval, query the tax and electricity ciphertext to obtain a ciphertext data set located in the query interval; and combine the ciphertext data sets according to the key fragmentation Decrypt to get the query results.

A tax and electricity data security fusion method according to an embodiment of the present invention calculates tax and electricity data fusion indicators by combining tax data and electricity data, and receives the key fragments obtained by splitting the order-preserving key according to the threshold secret sharing algorithm by the security query center, Perform joint encryption on the tax and electricity data fusion index according to the key fragmentation to obtain the tax and electricity ciphertext, and query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval, The ciphertext data set is jointly decrypted according to the key sharding to obtain query results, and the economic development status can be analyzed by querying tax and electricity data fusion indicators. Multiple tax and electricity nodes are split and protected through a threshold secret sharing algorithm. The key fragments obtained by the order key encrypt and decrypt the tax and electricity data fusion indicators. The order-preserving key requires multiple key fragments to obtain, so each tax and electricity node requires key fragments sent by other tax and electricity nodes. Only then can the order-preserving key be reconstructed, ensuring key security. Since encryption and decryption are performed through the order-preserving key, when querying tax and electricity data fusion indicators, you only need to query the ciphertext, and then query the ciphertext data. The query results can be obtained by decrypting the set. There is no need to decrypt all tax and electricity data fusion indicators to ensure data security.

In an optional embodiment, calculating tax and electricity data fusion indicators by combining tax data and electricity data includes: combining tax data and electricity data to calculate tax and electricity energy efficiency indicators, electricity consumption indicators and tax economic indicators. The calculation formula of the electrical energy efficiency index is:

In the formula, Represents tax electricity energy efficiency index,/> Indicates the electricity consumption in the tax period,/> Indicates the electricity consumption in this period; the calculation formula of the electricity consumption indicator is:

In the formula, Indicates the power consumption indicator,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of electricity users in this period,/> Indicates the number of electricity users in the same period,/> Indicates electricity consumption during the same period;

The calculation formula of the tax economic indicators is:

In the formula, Indicates tax economic indicators,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of tax users in the current period,/> Indicates the number of tax users in the same period,/> represents the tax electricity consumption during the same period; multiply the tax electricity energy efficiency index, the electricity consumption index and the tax economic index by the corresponding weight coefficients to obtain the tax electricity data fusion index. Calculation of the tax electricity data fusion index The formula is:

In the formula, Indicates tax and electricity data fusion indicators,/> ,/> ,/> Indicates the corresponding weight coefficient.

By combining tax data and electricity data to calculate tax and electricity energy efficiency indicators, electricity consumption indicators, tax economic indicators, tax and electricity data fusion indicators and other indicators, we can break up each other's data barriers and solve the pain points of single data. Tax and electricity data fusion indicators It is of great significance in the precise implementation of policies by service departments and the improvement of quality and efficiency of enterprises.

In an optional embodiment, the combination of tax data and electricity data to calculate tax energy efficiency indicators, electricity consumption indicators and tax economic indicators includes: generating a public-private key pair based on an approximate computing homomorphic encryption algorithm. The key pair includes a public key and a private key; the tax data and the power data are homomorphically encrypted according to the public key to obtain the tax data ciphertext and the power data ciphertext; based on the corresponding calculation formula, the tax data ciphertext and the power data are combined The ciphertext is fused and calculated to obtain the tax electricity energy efficiency index, electricity energy consumption index and tax economic index.

The tax data and power data are homomorphically encrypted using an approximate computing homomorphic encryption algorithm and then ciphertext fusion calculation is performed based on the ciphertext to ensure the data security of each tax and power node.

In an optional embodiment, jointly encrypting the tax and electricity data fusion indicators according to the key fragmentation to obtain the tax and electricity ciphertext includes: requesting to obtain other tax and electricity ciphertext based on the threshold value of the threshold secret sharing algorithm. The key fragmentation of the electricity node; the order-preserving key is calculated based on its own key fragmentation and the key fragmentation of other tax and electricity nodes; the tax and electricity data fusion index is obtained by encrypting the order-preserving key based on the key fragmentation Tax code cipher text.

Recover the order-preserving key by requesting the key fragments of other tax and electricity nodes. When encrypting data, you need to obtain the key fragments of other tax and electricity nodes to increase the security of the key.

In an optional embodiment, querying the tax ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval includes: sorting the local tax ciphertext based on equivalent data merging. The electronic ciphertext is sorted to obtain the locally sorted tax and electronic ciphertext; based on the received query interval, the locally sorted tax and electronic ciphertext is queried to obtain the ciphertext data set located in the query interval.

Through the sorting algorithm based on equivalent data merging, the tax and electricity ciphertext can be quickly sorted to improve query efficiency.

In an optional embodiment, the joint decryption of the ciphertext data set according to the key fragmentation to obtain the query result includes: requesting to obtain the information of other tax and electricity nodes based on the threshold value of the threshold secret sharing algorithm. Key fragmentation; calculate the order-preserving key based on its own key fragmentation and the key fragmentation of other tax and electricity nodes; decrypt the ciphertext data set based on the order-preserving key to obtain the query result.

By requesting the key shard decryption ciphertext data set of other tax and electricity nodes, local data query can be realized.

In an optional embodiment, jointly decrypting the ciphertext data set according to the key fragments to obtain query results includes: sending the key fragments and the ciphertext data set to a secure query center ; Use the security query center's sorting algorithm based on equivalent data merging to jointly sort the received ciphertext data sets sent by each tax and electricity node, and combine all the received ciphertext data sets sent by the other tax and electricity nodes through the security query center The key sharding is used to jointly decrypt the jointly sorted ciphertext data set to obtain the query result.

The security query center jointly sorts the received ciphertext data sets sent by each tax and electricity node, and uses the security query center to combine the key fragments sent by other tax and electricity nodes to jointly sort the ciphertext data sets. The text data set is jointly decrypted to obtain the query results, and the data of multiple tax and electricity nodes can be queried.

In the second aspect, the present invention provides a tax and electricity node based on the secure integration of tax and electricity data, including:

The indicator calculation module is used to calculate tax and electricity data fusion indicators by combining tax data and electricity data;

The key fragment receiving module is used to receive the key fragments obtained by the security query center by splitting the order-preserving key according to the threshold secret sharing algorithm;

A joint encryption module, configured to jointly encrypt the tax and electricity data fusion index according to the key fragmentation to obtain the tax and electricity ciphertext;

A query module, configured to query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval;

A joint decryption module, configured to jointly decrypt the ciphertext data set according to the key fragmentation to obtain query results.

In a third aspect, the present invention provides a computer device, including: a memory and a processor. The memory and the processor are communicatively connected to each other. Computer instructions are stored in the memory. The processor executes the instructions. The computer instructions are used to execute the tax and electricity data security fusion method provided by the first aspect of the present invention.

In a fourth aspect, the present invention provides a computer-readable storage medium, characterized in that computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause the computer to execute the tax method provided in the first aspect of the present invention. Electronic data security fusion method.

Description of the drawings

In order to more clearly explain the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings that need to be used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description The drawings illustrate some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

Figure 1 is a schematic flow chart of a tax and electricity method for securely integrating tax and electricity data according to an embodiment of the present invention;

Figure 2 is a schematic flowchart of another tax and electricity method for securely integrating tax and electricity data according to an embodiment of the present invention;

Figure 3 is a structural block diagram of a tax and electricity node based on the secure integration of tax and electricity data according to an embodiment of the present invention;

Figure 4 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the scope of protection of the present invention.

At present, both tax authorities and power grid companies have abundant data resources, and tax and electricity data are highly complementary. The two have high consistency in industry classification and national economic statistical standards, and have a good data integration foundation. The embodiment of the present invention constructs a tax and electricity data fusion index through the fusion analysis of tax and electricity data to measure the economic benefits brought by unit electricity consumption, social electricity energy consumption, social taxation and economic conditions, and social and economic development, and is accurate in the service department. It is of great significance in terms of policy implementation and enterprise improvement in quality and efficiency.

According to an embodiment of the present invention, a tax and electricity data security fusion method is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although A logical order is shown in the flowcharts, but in some cases, the steps shown or described may be performed in a different order than herein.

In this embodiment, a tax and electricity data security fusion method is provided, which is applied to a tax and electricity node in a tax and electricity system. The tax and electricity system includes multiple tax and electricity nodes, where the tax and electricity node can be an electric power set in the power grid. End equipment or tax end equipment set up in the tax department. The power end equipment stores local power data such as electricity consumption, industry expansion report and net added capacity, etc. The tax end equipment stores local tax data, such as invoice amount, The tax end device and the power end device can interact to obtain the local data ciphertext stored by each other, such as the number of taxpayers issuing invoices. Referring to Figures 1 and 2, the tax and electricity data security fusion method according to the embodiment of the present invention includes the following steps:

Step S101: Calculate tax and electricity data fusion indicators by combining tax data and electricity data.

Specifically, the data semantics, business logic and business goals of the tax and electricity data fusion business are analyzed, and relevant data fields distributed in different databases and different data tables are extracted according to the tax and electricity data fusion business logic and goals, including power operating data, Electric power expected data, tax operating data and tax expected data, such as invoice amount, number of taxpayers issuing invoices, electricity consumption, net increase in industry expansion report and installation capacity, etc., to build a tax and electricity data fusion business data space, in this data space Contains tax data and electricity data required to calculate tax and electricity data fusion indicators.

According to the tax and electricity data fusion business objectives, determine the interval distribution boundary values that need to be counted for the current business and the business data feature dimensions that require statistical analysis this time. The tax data and electricity data in the data space are integrated and compared to obtain a tax and electricity data summary table. The original data in the tax and electricity data summary table completes the calculation of tax and electricity energy efficiency indicators, monthly electricity consumption indicators, monthly tax indicators and other indicators of energy-consuming units through group statistics, linear combination, data operations and other aggregation operations. Construct a comprehensive table of tax and electricity data from multiple dimensions such as time, region, and industry, and count tax and electricity data fusion indicators at different times, spaces, and industries, thereby achieving yearly, quarterly, monthly, and other different time scales, different spatial regions, and industries. Analyze tax and electricity data from other angles, realize multi-dimensional analysis of electricity economics, and solve the problem of multi-party safe and efficient statistics of tax and electricity data under data compliance constraints.

Step S102: Receive the key fragments obtained by the security query center by splitting the order-preserving key according to the threshold secret sharing algorithm.

Specifically, the security query center, as a third-party security certification center, selects an order-preserving encryption algorithm to obtain the order-preserving key. , order-preserving key/> It is a symmetric key, that is, encryption and decryption share the same key. The security query center determines the holders of key shards, namely the number n of tax and electricity nodes and the threshold value k, and uses the Shamir threshold secret sharing algorithm to split the order-preserving keys. Get n key shards/> , each key fragment is sent to the corresponding holder, and each tax electricity node receives and stores one of the corresponding key fragments.

Among them, the Shamir threshold secret sharing algorithm is used to split the order-preserving key. The process of obtaining n key fragments includes:

Step 1: Randomly pick k-1 numbers in the finite field from 1 to p, recorded as ,/> ,…,/> , take it as the coefficient of the non-constant term of the k-1 degree polynomial f(x);

Step 2: Construct the polynomial as ...+/> ;

Step 3: n holders are recorded as , holder/> Get the subkey as/> .

Step S103: Jointly encrypt the tax and electricity data fusion indicators based on key fragmentation to obtain the tax and electricity ciphertext.

Specifically, according to the principle of the Shamir threshold secret sharing algorithm, each tax and electricity node needs to obtain at least k key shards to obtain an order-preserving key, that is, each tax and electricity node needs to combine at least k-1 other tax and electricity nodes. The electricity nodes jointly encrypt the tax and electricity data fusion indicators to obtain the tax and electricity ciphertext.

Step S104: Query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval.

Specifically, the query range is a query condition input directly by the user to the tax and electricity node to query the local data of the tax and electricity node; or a query condition input to the security query center to query the data stored in all tax and electricity nodes. In the former case, the local tax and electricity node joins other tax and electricity nodes to encrypt the query interval based on key sharding, and then compares the query interval ciphertext with the tax and electricity ciphertext to obtain the ciphertext data set. The query obtained The ciphertext data set is the tax and electricity ciphertext located in the query interval. In the latter case, the security query center encrypts the query interval in order and sends it to each tax and electricity node. Each tax and electricity node compares the encrypted query interval with its own saved tax and electricity ciphertext to obtain the query interval. The local ciphertext data set is then sent to the security query center, and the security query center integrates the received ciphertext data set.

Step S105: Jointly decrypt the ciphertext data set according to the key fragmentation to obtain the query result.

Specifically, when the user directly queries the local data from the tax and electricity node, the tax and electricity node needs to jointly decrypt the ciphertext data set with other k-1 tax and electricity nodes to obtain the query result. When the user inputs query conditions to the security query center, the tax and electricity node sends the key fragments and ciphertext data set to the security query center, and the security query center decrypts the ciphertext data set based on the received key fragments. , get the query results.

Through the query results, users can know the tax and electricity data fusion indicators of various time and space regions. The tax and electricity data fusion indicators calculated by combining tax data and electricity data can objectively analyze economic development.

A tax and electricity data security fusion method according to an embodiment of the present invention calculates tax and electricity data fusion indicators by combining tax data and electricity data, and receives the key fragments obtained by splitting the order-preserving key according to the threshold secret sharing algorithm by the security query center, The tax and electricity data fusion indicators are jointly encrypted according to the key fragmentation to obtain the tax and electricity ciphertext. Based on the received query interval, the ciphertext data set located in the query interval is obtained from the tax and electricity ciphertext. The ciphertext is encrypted according to the key fragmentation. The data set is jointly decrypted to obtain the query results, which can analyze the economic development status by querying the tax and electricity data fusion indicators. Multiple tax and electricity nodes use the key shards obtained by splitting the order-preserving keys based on the threshold secret sharing algorithm to analyze the tax and electricity data. Data fusion indicators are used for encryption and decryption. The order-preserving key requires multiple key fragments to obtain. Therefore, each tax electricity node needs key fragments sent by other tax electricity nodes to reconstruct the order-preserving key, ensuring the encryption The key is secure, and since encryption and decryption are performed through order-preserving keys, when querying tax and electricity data fusion indicators, you only need to query the ciphertext, and then decrypt the ciphertext data set obtained by the query to obtain the query results. There is no need to All tax and electricity data fusion indicators are decrypted to ensure data security.

In some optional embodiments, in step S101, calculating tax and electricity data fusion indicators by combining tax data and electricity data includes:

Step S1011, combine the tax data and electric power data to calculate the tax electricity energy efficiency index, electricity consumption index and tax economic index. The calculation formula of the tax electricity energy efficiency index is:

In the formula, Represents tax electricity energy efficiency index,/> Indicates the electricity consumption in the tax period,/> Indicates the electricity consumption in this period;

The calculation formula for the electricity consumption indicator is:

In the formula, Indicates the power consumption indicator,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of electricity users in this period,/> Indicates the number of electricity users in the same period,/> Indicates electricity consumption during the same period;

The calculation formula of tax economic indicators is:

In the formula, Indicates tax economic indicators,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of tax users in the current period,/> Indicates the number of tax users in the same period,/> Indicates electricity consumption during the tax period.

Step S1012: Multiply the tax and electricity energy efficiency index, the electricity consumption index and the tax economic index by the corresponding weight coefficients to obtain the tax and electricity data fusion index. The calculation formula of the tax and electricity data fusion index is:

In the formula, Indicates tax and electricity data fusion indicators,/> ,/> ,/> Indicates the corresponding weight coefficient.

Specifically, the tax electricity energy efficiency index Used to analyze the economic benefits brought by unit energy consumption, electricity consumption indicators Used to analyze social electricity energy consumption, tax economic indicators/> Used to analyze social taxation situations, and calculate tax and electricity energy efficiency indicators, electricity consumption indicators, tax economic indicators, tax and electricity data fusion indicators and other indicators by combining tax data and electricity data to break through each other's data barriers and solve the pain points of single data. Question, tax and electricity data integration indicators are of great significance in the precise implementation of policies by service departments and the improvement of quality and efficiency of enterprises.

Based on tax electricity energy efficiency index , Electricity consumption index/> , tax economic indicators/> Comprehensive calculation of tax and electricity data fusion indicators/> It can analyze the economic situation comprehensively based on taxation and electricity consumption. It can build a multi-dimensional analysis model of tax and electricity data fusion indicators from multiple dimensions such as time, region, and industry, and realize a comprehensive analysis of electricity taxation through different time scales such as annual, quarterly, and monthly. Multidimensional analysis of economics.

In some optional embodiments, in step S1011, tax data and power data are combined to calculate tax power efficiency indicators, power consumption indicators and tax economic indicators, including:

Step a1: Generate a public-private key pair based on the approximate computing homomorphic encryption algorithm. The public-private key pair includes a public key and a private key.

Specifically, choose a power N of 2, and a special modulus P, define , making N and/> Meet safety level/> ,Q is the scale of L layer module,/> is the divisor of Q, L is the ciphertext level,/> is the value of the defined basis at the Lth layer,/> For the security level parameter, select a private key related distribution/> , an error distribution/> , and then calculate the public-private key pair/> , the calculation process is as follows:

Step 1: Instantiate , and/> ;

Step 2: Set up private key ;

Step 3: Calculate the public key , where,/> .

in, Represents the distribution associated with the private key, /> Indicates compliance/> A sample of the distribution,/> represents an error distribution, /> Indicates compliance/> A sample of the distribution,/> Represents the private key,/> Represents the public key,/> Represents plaintext space,/> express Sample of space.

Step a2: Perform homomorphic encryption on the tax data and power data based on the public key to obtain the tax data ciphertext and power data ciphertext.

If the tax and electricity node is a power-end device, it receives the tax data ciphertext sent by the tax end node, encrypts its own power data, and exchanges its encrypted power data ciphertext to the corresponding tax end node. The node’s encryption process for tax data or power data is as follows:

Choose a random distribution Used for encryption, plaintext/> , generate/> , and/> , construct ciphertext/> .

in, Represents plaintext space, plaintext/> ,/> represents an error distribution, /> and/> Indicates compliance/> Distribution samples,/> Represents a random distribution,/> Indicates compliance/> A sample of the distribution,/> Represents cipher text.

Step a3: Based on the corresponding calculation formula, the tax data ciphertext and the electricity data ciphertext are combined to perform ciphertext fusion calculation to obtain the tax electricity energy efficiency index, electricity energy consumption index and tax economic index.

Energy efficiency indicators in calculating taxes , Electricity consumption index/> , tax economic indicators/> , Tax and electricity data fusion indicators/> When calculating other indicators, multiplication and addition operations are used. Therefore, when performing ciphertext calculations, three types of operators need to be applied: ciphertext addition, ciphertext and plaintext multiplication, and ciphertext and ciphertext multiplication. Through these three types of operators, Sub-construct the ciphertext statistical calculation logic to perform ciphertext fusion calculation, and obtain the tax electricity energy efficiency index, electricity consumption index and tax economic index. The calculation formulas of the three types of operators are as follows:

in, Represents plaintext space,/> Represents ciphertext space, plaintext/> , two ciphertexts/> , Represents the ciphertext sum,/> Represents the multiplication of ciphertext and plaintext,/> Represents the multiplication of ciphertext and ciphertext,/> Represents the auxiliary key,/> ,/> and/> Indicates ciphertext/> and/> The middle value of /> Indicates rounding.

Based on the ciphertext fusion calculation, the ciphertext of the tax and electricity energy efficiency index, the electricity consumption index and the tax economic indicator are obtained. The ciphertext of the tax and electricity data fusion index is calculated according to the calculation formula of the tax and electricity data fusion index. Then, Decrypt it through the private key to obtain the decrypted tax and electricity data fusion index.

In the ciphertext operation, the ciphertext addition, multiplication of ciphertext and ciphertext, and multiplication of ciphertext and plaintext of the homomorphic encryption algorithm are used to realize the ciphertext fusion calculation of tax and electricity data. The ciphertext calculation result is decrypted by the private key. , through mutual restraint between encryption and decryption parties, the data confidentiality capabilities of multi-subject tax and electricity data are strengthened. The tax data and electricity data are homomorphically encrypted using an approximate computing homomorphic encryption algorithm and then the ciphertext fusion calculation is performed based on the ciphertext. Each tax and electricity node only receives the ciphertext of the data sent by other tax and electricity nodes and cannot know the plaintext. This ensures the data security of each tax and electricity node when calculating tax and electricity data fusion indicators.

In some optional embodiments, step S103, perform joint encryption on tax and electricity data fusion indicators based on key fragmentation to obtain tax and electricity ciphertext, including:

Step S1031: Based on the threshold value of the threshold secret sharing algorithm, request to obtain the key shards of other tax and electricity nodes.

For example, the threshold value of the threshold secret sharing algorithm is k, and the tax electricity node needs to encrypt the tax electricity data fusion index with the assistance of k key shards. Therefore, the tax electricity node needs to provide information to other k-1 tax electricity nodes. Initiate a request to obtain the corresponding key shard. Other tax and electricity nodes agree to the encryption request and return their own key fragments to the tax and electricity node that initiated the request.

Step S1032: Calculate the order-preserving key based on its own key fragments and the key fragments of other tax and electricity nodes.

Specifically, the calculation formula for recovering the order-preserving key through k key fragments is:

in, Represents an order-preserving key,/> Represents the i-th key fragment.

Step S1033: Encrypt the tax and electricity data fusion index based on the order-preserving key to obtain the tax and electricity ciphertext.

It can be understood that after the order-preserving key is recovered, the tax and electricity data fusion indicators are encrypted based on the order-preserving key to obtain the tax and electricity ciphertext. For example, the tax and electricity node j encrypts the hydropower integration index x with the assistance of k key shards, and the process of outputting the electricity ciphertext y is expressed as:

Recover the order-preserving key by requesting the key fragments of other tax and electricity nodes. When encrypting data, you need to obtain the key fragments of other tax and electricity nodes to increase the security of the key.

In some optional embodiments, step S104, query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval, including:

Step S1041, the local tax and electricity ciphertext is sorted based on the sorting algorithm of equivalent data merging to obtain the locally sorted tax and electricity ciphertext.

Specifically, the sorting algorithm based on equivalent data merging uses the idea of divide and conquer method to split the tax and electricity ciphertext combination sequence into two parts in each round, and then sort the left part through recursion, and then Arrange the order of the right part recursively, and achieve efficient sorting of tax and electricity ciphertext through multiple comparisons and exchanges.

Step S1042: Based on the received query interval, query the locally sorted tax and electricity ciphertext to obtain the ciphertext data set located in the query interval.

Specifically, the order-preserving encrypted ciphertext itself has sorting properties. By performing order-preserving encryption on the query interval, the query interval ciphertext is obtained. By comparing the query interval ciphertext with the sorted tax and electricity ciphertext, the query interval can be obtained. ciphertext data set.

Through the sorting algorithm based on equivalent data merging, the tax and electricity ciphertext can be quickly sorted to improve the stability and efficiency of quick sort retrieval.

In some optional embodiments, step S105, jointly decrypt the ciphertext data set according to key fragmentation to obtain query results, including:

Step b1: Based on the threshold value of the threshold secret sharing algorithm, request to obtain the key shards of other tax and electricity nodes.

Step b2: Calculate the order-preserving key based on its own key fragments and the key fragments of other tax and electricity nodes.

Step b3: Decrypt the ciphertext data set based on the order-preserving key to obtain the query result.

Specifically, this embodiment is used when the user directly queries the tax and electricity node for local data. The threshold value of the threshold secret sharing algorithm is k. The tax electricity node needs to encrypt the tax electricity data fusion indicator with the assistance of k key shards. Therefore, the tax electricity node needs to initiate a request to other k-1 tax electricity nodes to obtain The corresponding key shard. Other tax and electricity nodes agree to the encryption request and return the key fragments to the tax and electricity node that initiated the request. After obtaining k key fragments, the calculation formula for recovering the order-preserving key is:

After obtaining the order-preserving key, decrypt the ciphertext data set using the order-preserving key to obtain the query result. The formula is as follows:

in, Represents an order-preserving key,/> Represents the i-th key fragment,/> ,/> Represents the ciphertext data set and query results respectively,/> Represents the modulus.

By requesting the key shard decryption ciphertext data set of other tax and electricity nodes, local data query can be realized.

In some optional embodiments, step S105, jointly decrypt the ciphertext data set according to key fragmentation to obtain query results, including:

Step c1: Send the key fragment and ciphertext data set to the security query center.

Step c2: Jointly sort the received ciphertext data sets sent by each tax and electricity node through the security query center's sorting algorithm based on equivalent data merging, and combine the key shard pairs sent by other tax and electricity nodes through the security query center. The jointly sorted ciphertext data sets are jointly decrypted to obtain the query results.

Specifically, this embodiment is suitable for the scenario of querying the security center for data of all tax and electricity nodes.

The user enters the query conditions into the security query center. The security query center encrypts the query conditions and sends them to each tax and electricity node. Each tax and electricity node compares the encrypted query interval with its own sorted tax and electricity ciphertext. , obtain the local ciphertext data set located in the query interval, and then send the ciphertext data set and respective key fragments to the security query center, and use the security query center's sorting algorithm based on equivalent data merging to sort each received tax The ciphertext data sets sent by the electrical nodes are jointly sorted. The ciphertext data sets sent by each tax and electricity node have been sorted before being sent to the security query center. The security query center needs to jointly sort the ciphertext data sets sent by each tax and electricity node based on the sorting algorithm of equivalent data merging. The jointly sorted ciphertext data set is jointly decrypted with the key fragments sent by other tax and electricity nodes to obtain the query results. The decryption process is the same as in the above embodiment. The query results output by the security query center include the data saved by each tax and electricity node that conforms to the query range, and can conduct an overall query of the data of all tax and electricity nodes. The security query center restores the order-preserving key and decrypts the process as follows:

in, Represents an order-preserving key,/> Represents the i-th key fragment,/> ,/> Respectively represent the tax and electricity data fusion indicators, namely plain text and tax and electricity cipher text,/> Represents the modulus.

The security query center jointly sorts the received ciphertext data sets sent by each tax and electricity node, and the security query center combines the key fragments sent by other tax and electricity nodes to jointly decrypt the jointly sorted ciphertext data set. Get the query results and query the data of multiple tax and electricity nodes.

The implementation process of the tax and electricity data security fusion method according to the embodiment of the present invention will be described below with reference to a specific application example.

Assume that there are tax and electricity nodes including tax end equipment in Province A, power end equipment in Province A, power end equipment in Province B, and tax end equipment in Province B for secure integration of tax and electricity data.

The specific implementation plan is:

(1) According to the tax and electricity data fusion business data space, the tax end equipment of Province A, the electric power end equipment of Province A, the electric power end equipment of Province B, and the tax end equipment of Province B extract business data fields locally from their respective databases.

(2) Construct a public-private key pair based on the approximate computing homomorphic encryption algorithm CKKS .

(3) All parties pass the public key Encrypt local data for ciphertext exchange.

(4) Calculate the tax power efficiency index based on three types of operators: ciphertext addition, ciphertext and plaintext multiplication, and ciphertext and ciphertext multiplication. , Electricity consumption index/> , tax economic indicators/> .

(5) According to the tax and electricity data fusion business, perform homomorphic ciphertext aggregation operations to calculate the statistical characteristics of tax and electricity data and obtain tax and electricity data fusion indicators. .

(6) Select the order-preserving encryption algorithm and obtain the order-preserving key , use the Shamir threshold secret sharing algorithm to split the order-preserving key/> , generate 4 key shards/> .

(7) All parties use key sharding to jointly encrypt tax and electricity data fusion indicators to obtain tax and electricity ciphertext, and perform local sorting and storage based on the quick sorting algorithm of equivalent data merging.

(8) According to the joint retrieval requirements of tax and electricity data ciphertext, that is, the query interval, the distributed joint retrieval of tax and electricity ciphertext is realized by introducing equivalent data retrieval and merging measures before the quick sort algorithm.

(9) Recover the key through k key shares , decrypt the plain text of the retrieved tax and electricity ciphertext, and obtain the query results.

In another application scenario, the query interval can be sent to each tax and electricity node through the security query center. Each tax and electricity node compares the encrypted query interval with the sorted tax and electricity ciphertext stored in it to obtain the tax and electricity cipher text located in the query interval. The local ciphertext data set is then sent to the security query center. The security query center then jointly sorts the obtained ciphertext data set and combines it with the provincial tax and electricity platforms. Run the multi-party data order-preserving encryption mechanism decryption algorithm to obtain the query results.

The tax and electricity data security fusion method of the embodiment of the present invention takes into account the rapid sorting of multi-party ciphertext and the data security protection needs of all parties, and introduces threshold key technology and order-preserving encryption technology into the tax and electricity data fusion business. By using order-preserving encryption The key is designed as a threshold key, and a (k, n) threshold encryption and decryption scheme is constructed. The tax-electricity fusion data is jointly encrypted through k key shards of the order-preserving key, thereby realizing the application of the order-preserving encryption algorithm to multi-party encryption and decryption. scenarios, key security can be ensured during data fusion and query.

The ciphertext sorting scheme based on quick sort uses the divide-and-conquer method to achieve efficient retrieval and analysis of large-scale ciphertext.

Moreover, the tax and electricity data security fusion method of the embodiment of the present invention breaks through each other's data barriers by combining tax data and electricity data to calculate tax and electricity energy efficiency indicators, electricity consumption indicators, tax economic indicators, tax and electricity data fusion indicators and other indicators. , to solve the pain points of single data, tax and electricity data integration indicators are of great significance in the precise implementation of policies by service departments and the improvement of quality and efficiency of enterprises.

This embodiment also provides a tax and electricity node based on the secure integration of tax and electricity data, which is used to implement the above embodiments and preferred implementations. What has already been explained will not be described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

An embodiment of the present invention also provides a tax and electricity node based on the secure integration of tax and electricity data, as shown in Figure 3, including:

The indicator calculation module 301 is used to calculate tax and electricity data fusion indicators by combining tax data and electricity data;

The key fragment receiving module 302 is used to receive the key fragments obtained by the security query center by splitting the order-preserving key according to the threshold secret sharing algorithm;

The joint encryption module 303 is used to jointly encrypt the tax and electricity data fusion indicators based on key fragmentation to obtain the tax and electricity ciphertext;

The query module 304 is configured to query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval;

The joint decryption module 305 is used to jointly decrypt the ciphertext data set according to the key fragmentation to obtain the query result.

A tax and electricity node based on the secure fusion of tax and electricity data according to the embodiment of the present invention calculates the tax and electricity data fusion index by combining tax data and electricity data, and receives the secret key obtained by the security query center by splitting the order-preserving key according to the threshold secret sharing algorithm. Key fragmentation, jointly encrypt the tax and electricity data fusion indicators according to the key fragmentation to obtain the tax and electricity ciphertext, query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval, and obtain the ciphertext data set located in the query interval based on the key fragmentation The query results are obtained by jointly decrypting the ciphertext data set, and the economic development status can be analyzed by querying the tax and electricity data fusion indicators. Multiple tax and electricity nodes split the order-preserving keys based on the threshold secret sharing algorithm to obtain the key analysis. Slices encrypt and decrypt tax and electricity data fusion indicators. The order-preserving key requires multiple key fragments to obtain. Therefore, each tax and electricity node requires key fragments sent by other tax and electricity nodes to reconstruct the order-preserving key. , ensuring the security of the key, and since encryption and decryption are performed through order-preserving keys, when querying tax and electricity data fusion indicators, you only need to query the ciphertext, and then decrypt the ciphertext data set obtained from the query to obtain the query results. , there is no need to decrypt all tax and electricity data fusion indicators to ensure data security.

In some optional embodiments, the indicator calculation module 301 includes:

The first calculation module is used to calculate tax electricity energy efficiency indicators, electricity consumption indicators and tax economic indicators by combining tax data and electricity data. The calculation formula of tax electricity energy efficiency indicators is:

In the formula, Represents tax electricity energy efficiency index,/> Indicates the electricity consumption in the tax period,/> Indicates the electricity consumption in this period;

The calculation formula for the electricity consumption indicator is:

In the formula, Indicates the power consumption indicator,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of electricity users in this period,/> Indicates the number of electricity users in the same period,/> Indicates electricity consumption during the same period;

The calculation formula of tax economic indicators is:

In the formula, Indicates tax economic indicators,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of tax users in the current period,/> Indicates the number of tax users in the same period,/> Indicates the electricity consumption during the tax period;

The second calculation index module is used to multiply the tax and electricity energy efficiency indicators, electricity consumption indicators and tax economic indicators by the corresponding weight coefficients to obtain the tax and electricity data fusion index. The calculation formula of the tax and electricity data fusion index is:

In the formula, Indicates tax and electricity data fusion indicators,/> ,/> ,/> Indicates the corresponding weight coefficient.

In some optional embodiments, the first computing module includes:

The key building module is used to generate a public-private key pair based on the approximate computing homomorphic encryption algorithm. The public-private key pair includes a public key and a private key;

The homomorphic encryption module is used to homomorphically encrypt tax data and power data based on the public key to obtain tax data ciphertext and power data ciphertext;

The third calculation module is used to perform ciphertext fusion calculation based on the corresponding calculation formula, combined with the tax data ciphertext and the power data ciphertext, to obtain tax and electricity energy efficiency indicators, electricity energy consumption indicators and tax economic indicators.

In some optional embodiments, the joint encryption module 303 includes:

The first shard acquisition module is used to request the key shards of other tax and electricity nodes based on the threshold value of the threshold secret sharing algorithm;

The first key reconstruction module is used to calculate the order-preserving key based on its own key fragments and the key fragments of other tax and electricity nodes;

The order-preserving encryption module is used to encrypt the tax and electricity data fusion indicators based on the order-preserving key to obtain the tax and electricity ciphertext.

In some optional embodiments, query module 304 includes:

The first sorting module is used to sort the local tax and electricity ciphertext based on the sorting algorithm of equivalent data merging to obtain the locally sorted tax and electricity ciphertext;

The interval comparison module is used to query the locally sorted tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval.

In some optional embodiments, the joint decryption module 305 includes:

The second shard acquisition module requests to obtain the key shards of other tax and electricity nodes based on the threshold value of the threshold secret sharing algorithm;

The second key reconstruction module calculates the order-preserving key based on its own key fragments and the key fragments of other tax and electricity nodes;

The order-preserving decryption module is used to decrypt the ciphertext data set based on the order-preserving key to obtain query results.

In some optional embodiments, the joint decryption module 305 includes:

The sending module is used to send key fragments and ciphertext data sets to the security query center;

The joint decryption module is used to jointly sort the received ciphertext data sets sent by each tax and electricity node through the security query center's sorting algorithm based on equivalent data merging, and combine the keys sent by other tax and electricity nodes through the security query center The shards jointly decrypt the jointly sorted ciphertext data set to obtain the query results.

Further functional descriptions of the above-mentioned modules and units are the same as those in the above-mentioned corresponding embodiments, and will not be described again here.

Please refer to Figure 4. Figure 4 is a schematic structural diagram of a computer device provided by an embodiment of the present invention. As shown in Figure 4, the computer device includes: one or more processors 10, a memory 20, and a device for connecting various components. interfaces, including high-speed interfaces and low-speed interfaces. Various components communicate with each other using different buses and can be installed on a common motherboard or in other ways as needed. The processor may process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative implementations, multiple processors and/or multiple buses may be used with multiple memories and multiple memories, if desired. Likewise, multiple computer devices may be connected, each device providing part of the necessary operation (eg, as a server array, a set of blade servers, or a multi-processor system). In Figure 4, a processor 10 is taken as an example.

The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The above-mentioned hardware chip can be an application-specific integrated circuit, a programmable logic device or a combination thereof. The above-mentioned programmable logic device may be a complex programmable logic device, a field programmable logic gate array, a general array logic or any combination thereof.

The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

The memory 20 may include a program storage area and a data storage area, where the program storage area may store an operating system and an application program required for at least one function; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some optional implementations, the memory 20 may optionally include memories remotely located relative to the processor 10 , and these remote memories may be connected to the computer device through a network. Examples of the above-mentioned networks include but are not limited to the Internet, intranets, local area networks, mobile communication networks and combinations thereof.

The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memories.

The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.

Embodiments of the present invention also provide a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware or firmware, or can be recorded in a storage medium, or can be implemented as original storage downloaded through the network. Computer code in a remote storage medium or a non-transitory machine-readable storage medium and to be stored in a local storage medium such that the methods described herein may be stored on a computer using a general purpose computer, a special purpose processor, or programmable or special purpose hardware Such software processing on storage media. The storage medium may be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk or a solid state drive, etc.; further, the storage medium may also include a combination of the above types of memories. It can be understood that a computer, processor, microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by the computer, processor or hardware, the above implementations are implemented. The method illustrated.

Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the appended rights. within the scope of the requirements.

Claims (10)

1. A tax and electricity data security fusion method, applied to a tax and electricity node in a tax and electricity system. The tax and electricity system includes multiple tax and electricity nodes, which is characterized by including: Calculate tax and electricity data fusion indicators by combining tax data and electricity data; Receive the key fragments obtained by splitting the order-preserving key according to the threshold secret sharing algorithm by the security query center; Jointly encrypt the tax and electricity data fusion indicators according to the key fragmentation to obtain the tax and electricity ciphertext; Based on the received query interval, query the tax and electricity ciphertext to obtain the ciphertext data set located in the query interval; The ciphertext data set is jointly decrypted according to the key fragmentation to obtain the query result. 2. The method according to claim 1, wherein calculating the tax and electricity data fusion index by combining tax data and electricity data includes: The tax data and electricity data are combined to calculate the tax electricity energy efficiency index, electricity consumption index and tax economic index. The calculation formula of the tax electricity energy efficiency index is: In the formula, Represents tax electricity energy efficiency index,/> Indicates the electricity consumption in the tax period,/> Indicates the electricity consumption in this period; The calculation formula of the electricity consumption indicator is: In the formula, Indicates the power consumption indicator,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of electricity users in this period,/> Indicates the number of electricity users in the same period,/> Indicates electricity consumption during the same period; The calculation formula of the tax economic indicators is: In the formula, Indicates tax economic indicators,/> ,/> Indicates the corresponding weight coefficient,/> Indicates the number of tax users in the current period,/> Indicates the number of tax users in the same period,/> Indicates the electricity consumption during the tax period; The tax and electricity energy efficiency index, the electricity consumption index and the tax economic indicator are multiplied by the corresponding weight coefficients to obtain the tax and electricity data fusion index. The calculation formula of the tax and electricity data fusion index is: In the formula, Indicates tax and electricity data fusion indicators,/> ,/> ,/> Indicates the corresponding weight coefficient. 3. The method according to claim 2, characterized in that the combination of tax data and power data to calculate tax power efficiency indicators, power consumption indicators and tax economic indicators includes: Generate a public-private key pair based on an approximate computing homomorphic encryption algorithm, where the public-private key pair includes a public key and a private key; Perform homomorphic encryption on tax data and power data based on the public key to obtain tax data ciphertext and power data ciphertext; Based on the corresponding calculation formula, the ciphertext fusion calculation is performed by combining the tax data ciphertext and the electricity data ciphertext to obtain the tax electricity energy efficiency index, electricity energy consumption index and tax economic index. 4. The method according to claim 1, wherein the joint encryption of the tax and electricity data fusion index according to the key fragmentation to obtain the tax and electricity ciphertext includes: Based on the threshold value of the threshold secret sharing algorithm, request to obtain the key shards of other tax and electricity nodes; The order-preserving key is calculated based on its own key fragmentation and the key fragmentation of other tax and electricity nodes; The tax and electricity data fusion index is encrypted based on the order-preserving key to obtain the tax and electricity ciphertext. 5. The method according to claim 1, characterized in that querying the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval includes: The sorting algorithm based on equivalent data merging sorts the local tax and electricity ciphertext to obtain the locally sorted tax and electricity ciphertext; Based on the received query interval, the ciphertext data set located in the query interval is obtained from the locally sorted tax and electricity ciphertext. 6. The method according to claim 1, wherein the joint decryption of the ciphertext data set according to the key fragmentation to obtain the query result includes: Based on the threshold value of the threshold secret sharing algorithm, request to obtain the key shards of other tax and electricity nodes; The order-preserving key is calculated based on its own key fragmentation and the key fragmentation of other tax and electricity nodes; Decrypt the ciphertext data set based on the order-preserving key to obtain query results. 7. The method according to claim 1, wherein the joint decryption of the ciphertext data set according to the key fragmentation to obtain the query result includes: Send the key fragments and ciphertext data set to the security query center; The security query center uses a sorting algorithm based on equivalent data merging to jointly sort the received ciphertext data sets sent by each tax and electricity node, and combines the received ciphertext data sets sent by other tax and electricity nodes through the security query center. Key sharding jointly decrypts the jointly sorted ciphertext data set to obtain the query result. 8. A tax and electricity node based on the secure integration of tax and electricity data, which is characterized by including: The indicator calculation module is used to calculate tax and electricity data fusion indicators by combining tax data and electricity data; The key fragment receiving module is used to receive the key fragments obtained by the security query center by splitting the order-preserving key according to the threshold secret sharing algorithm; A joint encryption module, configured to jointly encrypt the tax and electricity data fusion index according to the key fragmentation to obtain the tax and electricity ciphertext; A query module, configured to query the tax and electricity ciphertext based on the received query interval to obtain the ciphertext data set located in the query interval; A joint decryption module, configured to jointly decrypt the ciphertext data set according to the key fragmentation to obtain query results. 9. A computer device, characterized in that it includes: A memory and a processor, the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes any one of claims 1 to 7 by executing the computer instructions. The tax and electricity data security fusion method. 10. A computer-readable storage medium, characterized in that computer instructions are stored on the computer-readable storage medium, and the computer instructions are used to cause the computer to execute the tax code described in any one of claims 1 to 7. Data security fusion approach.