CN116933299A - Tax electric data safety fusion method, tax electric node, equipment and medium - Google Patents
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Abstract
The invention relates to the technical field of information security, and discloses a tax data security fusion method, a tax node, equipment and a medium, wherein the method comprises the following steps: calculating tax-electricity data fusion indexes by combining tax data and electric power data; receiving a key fragment obtained by the security query center according to a threshold secret sharing algorithm by splitting the order-preserving key; performing joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext; inquiring from the tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval; and carrying out joint decryption on the ciphertext data set according to the key fragment to obtain a query result. The invention can ensure the security of the secret key and the data by encrypting and decrypting the order-preserving secret key based on the threshold secret sharing algorithm.
Description
Technical Field
The invention relates to the technical field of information security, in particular to a tax data security fusion method, a tax node device and a tax data security fusion medium.
Background
With the development of big data, the data becomes a new production element, and in recent years, related guidance opinion demands continuously strengthen the deep application of big data technology in the fields of economic operation research and judgment, social management and the like, and a new generation of digital technology infrastructure which is agile, efficient and reusable is built.
The tax department and the power grid company all have rich data resources such as platforms, users, data, brands and the like, the tax and electric power data are large in scale and various in variety, the characteristics of comprehensiveness, high frequency, real time, accuracy and the like are achieved, and the data of the two parties are centrally managed, unified in standard and easy to collect. The tax and electric data have good complementarity, and the tax and electric data have higher consistency with national economy statistics standards in industry classification and have better data fusion basis, so that the tax and electric data fusion index is constructed through fusion analysis of the tax and electric data, and the tax and electric data fusion index has important significance in the aspects of accurate construction of service departments, quality improvement and efficiency enhancement of enterprises and the like.
The order-preserving encryption is a ciphertext inquiry encryption method, and the ciphertext size relationship reflects the plaintext size relationship. In practical application, the data owner needs to send the secret key to the data user, and decrypt the retrieved ciphertext set to obtain the statistical result. But the data users may be malicious, and the current order-preserving encryption cannot be applied to multi-user scenes. Therefore, the confidentiality requirement of data of all parties is required to be met under an energy architecture, and the security of the secret key is ensured while ciphertext inquiry is realized.
Disclosure of Invention
In view of the above, the invention provides a tax electric data safety fusion method, tax electric node, equipment and medium, which are used for solving the technical problem that the safety of a secret key cannot be ensured when data fusion and inquiry are carried out under a multi-user scene by order-preserving encryption in the existing scheme.
In a first aspect, the present invention provides a tax data security fusion method, which is applied to a tax node in a tax system, where the tax system includes a plurality of tax nodes, and the tax data security fusion method includes: calculating tax-electricity data fusion indexes by combining tax data and electric power data; receiving a key fragment obtained by the security query center according to a threshold secret sharing algorithm by splitting the order-preserving key; performing joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext; inquiring from the tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval; and carrying out joint decryption on the ciphertext data set according to the key fragment to obtain a query result.
According to the tax data safety fusion method, tax data and electric power data are combined to calculate tax data fusion indexes, a safety query center receives key fragments obtained by splitting order-preserving keys according to a threshold secret sharing algorithm, the tax data fusion indexes are encrypted in a combined mode according to the key fragments to obtain tax ciphertexts, a ciphertext data set positioned in the query interval is queried from the tax ciphertexts based on the received query interval, the ciphertext data set is decrypted in a combined mode according to the key fragments to obtain query results, the economic development condition can be analyzed through querying the tax data fusion indexes, a plurality of tax nodes can encrypt and decrypt the tax data fusion indexes through the key fragments obtained by splitting the order-preserving keys based on the threshold secret sharing algorithm, the order-preserving keys can be obtained only by the key fragments, therefore, each electric node can reconstruct the order-preserving keys only by the key fragments sent by other tax nodes, the key safety is guaranteed, and the tax data can be decrypted without decrypting the query results by the order-preserving keys.
In an alternative embodiment, the calculating the tax data fusion index by combining tax data and power data includes: the tax electric energy efficiency index, the electricity consumption index and the tax economic index are calculated by combining tax data and electric power data, and the calculation formula of the tax electric energy efficiency index is as follows:
in the method, in the process of the invention,represents tax electric energy efficiency index->Indicating tax electricity consumption in the period of time, +.>Representing the electricity consumption of the electric power in the period; the calculation formula of the electricity consumption index is as follows:
in the method, in the process of the invention,indicating the power consumption index->、/>Representation ofCorresponding weight coefficient, ++>Indicating the number of users in the current period of power,/-, and>representing the number of power synchronous users, ">Representing the synchronous electricity consumption of the electric power;
the calculation formula of the tax economic index is as follows:
in the method, in the process of the invention,indicating tax economy index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the tax period>Representing tax contemporaneous user number,/->Representing tax contemporaneous electricity consumption; multiplying the tax electric energy efficiency index, the electric energy consumption index and the tax economic index by corresponding weight coefficients respectively to obtain a tax electric data fusion index, wherein the calculation formula of the tax electric data fusion index is as follows:
in the method, in the process of the invention,indicating tax electric data fusion index->、/>、/>Representing the corresponding weight coefficients.
By combining tax data and electric power data to calculate tax electric energy efficiency indexes, electric energy consumption indexes, tax economic indexes, tax electric data fusion indexes and other indexes, the data barriers of each other are opened, the pain point problem existing in single data is solved, and the tax electric data fusion indexes have important significance in the aspects of accurate construction of service departments, quality improvement and efficiency enhancement of enterprises and the like.
In an alternative embodiment, the calculating tax electrical energy efficiency index, electricity consumption index and tax economic index by combining tax data and electric power data includes: generating a public-private key pair based on an approximate calculation homomorphic encryption algorithm, wherein the public-private key pair comprises a public key and a private key; homomorphic encryption is carried out on tax data and electric power data according to the public key to obtain tax data ciphertext and electric power data ciphertext; and carrying out ciphertext fusion calculation by combining the tax data ciphertext and the electric power data ciphertext based on the corresponding calculation formula to obtain the tax electric energy efficiency index, the electric energy consumption index and the tax economic index.
And homomorphic encryption algorithm is approximately calculated to homomorphic encrypt tax data and electric power data, and ciphertext fusion calculation is carried out based on ciphertext, so that the data security of each tax node is ensured.
In an optional embodiment, the performing joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext includes: requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm; obtaining a sequence-preserving key according to the key fragments of the self and the key fragments of other tax nodes; and encrypting the tax data fusion index based on the order-preserving key to obtain a tax ciphertext.
And recovering the order-preserving key by requesting to acquire the key fragments of other tax nodes, and acquiring the key fragments of other tax nodes when encrypting data, thereby increasing the security of the key.
In an optional embodiment, the querying, based on the received query interval, from the tax ciphertext to obtain the ciphertext data set located in the query interval includes: sorting the local tax ciphertext based on the equivalent data merging sorting algorithm to obtain a local sorted tax ciphertext; inquiring from the locally ordered tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval.
And the quick ordering of tax ciphertext is realized by an ordering algorithm based on equivalent data merging, so that the query efficiency is improved.
In an optional embodiment, the performing joint decryption on the ciphertext data set according to the key fragment to obtain a query result includes: requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm; obtaining a sequence-preserving key according to the key fragments of the self and the key fragments of other tax nodes; and decrypting the ciphertext data set based on the order-preserving key to obtain a query result.
And obtaining the key fragment decryption ciphertext data set of other tax nodes by request to realize local data query.
In an optional embodiment, the performing joint decryption on the ciphertext data set according to the key fragment to obtain a query result includes: the key fragments and the ciphertext data set are sent to a security query center; and carrying out joint sorting on the ciphertext data sets sent by each received tax node through a sorting algorithm based on equivalent data merging of the security query center, and carrying out joint decryption on the jointly sorted ciphertext data sets by combining the key fragments sent by other tax nodes through the security query center to obtain a query result.
And carrying out joint sorting on the ciphertext data sets sent by the tax nodes through a security query center, and carrying out joint decryption on the jointly sorted ciphertext data sets by combining the key fragments sent by other tax nodes through the security query center to obtain a query result, thereby realizing the query on the data of a plurality of tax nodes.
In a second aspect, the present invention provides a tax node based on tax data security fusion, including:
the index calculation module is used for calculating tax data fusion indexes by combining tax data and electric power data;
the key fragment receiving module is used for receiving the key fragments obtained by the security inquiry center through splitting the order-preserving key according to the threshold secret sharing algorithm;
the joint encryption module is used for carrying out joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext;
the query module is used for querying from the tax ciphertext based on the received query interval to obtain a ciphertext data set positioned in the query interval;
and the joint decryption module is used for joint decrypting the ciphertext data set according to the key fragment to obtain a query result.
In a third aspect, the present invention provides a computer device comprising: the system comprises a memory and a processor, wherein the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions so as to execute the tax electric data safety fusion method provided by the first aspect of the invention.
In a fourth aspect, the present invention provides a computer readable storage medium, where computer instructions are stored on the computer readable storage medium, where the computer instructions are configured to cause a computer to execute the tax data security fusion method provided in the first aspect of the present invention.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a tax data security fusion tax method according to an embodiment of the invention;
FIG. 2 is a flow chart of another tax data security fusion tax method according to an embodiment of the invention;
FIG. 3 is a block diagram of a tax node based on tax data security fusion according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, tax departments and power grid companies have rich data resources, tax and electric power data have good complementarity, and the tax and electric power data have higher consistency with national economic statistical standards in industry classification and have better data fusion foundation. The tax electricity data fusion index is constructed through fusion analysis of tax and electric power data so as to measure economic benefits, social electricity consumption conditions, social tax economic conditions and social economic development conditions brought by unit electricity consumption, and the tax electricity data fusion index has important significance in the aspects of accurate construction of service departments, quality improvement and efficiency enhancement of enterprises and the like.
According to an embodiment of the present invention, there is provided a tax data security fusion method, it being noted that the steps shown in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.
The tax electric system comprises a plurality of tax electric nodes, wherein the tax electric nodes can be electric power end equipment arranged on a power grid or tax end equipment arranged on a tax department, the electric power end equipment stores local electric power data such as electricity consumption, business expansion, net increase capacity and the like, the tax end equipment stores local tax data such as invoice amount, invoicing tax amount and the like, and the tax end equipment and the electric power end equipment can interact to obtain local data ciphertext stored by each other. Referring to fig. 1 and 2, the tax data security fusion method according to the embodiment of the invention includes the following steps:
Step S101, tax data and electric power data are combined to calculate tax electric data fusion indexes.
Specifically, the data semantics, service logic and service targets of the tax electric data fusion service are analyzed, relevant data fields distributed in different databases and different data tables are extracted according to the tax electric data fusion service logic and targets, the relevant data fields comprise electric power management data, electric power expected data, tax management data and tax expected data, specifically, tax data and electric power data required by calculating tax electric data fusion indexes are constructed in the tax electric data fusion service data space, such as invoice amount, invoice taxpayer amount, electric power consumption, business expansion and net increase capacity and the like.
Determining interval distribution boundary values which need to be counted by the current business and business data feature dimensions which need to be counted and analyzed at the time according to a tax electric data fusion business target, integrating and comparing tax data and electric data in a data space to obtain a tax electric data summary table, and calculating indexes such as tax electric energy efficiency indexes, month electric indexes and month tax indexes of energy units by grouping statistics, linear combination, data operation and other aggregation operations of original data in the tax electric data summary table. The tax data summary table is constructed from multiple dimensions of time, area, industry and the like, tax data fusion indexes of different time, space and industry are counted, tax data are analyzed from different time scales of the year, quarter, month and the like, different space areas of the industry and the like, multidimensional analysis of electricity economy is realized, and the problem of multi-party safe and efficient statistics of the tax data under the data compliance regulation is solved.
Step S102, a key fragment obtained by the security query center according to the split order-preserving key of the threshold secret sharing algorithm is received.
Specifically, the security query center is used as a third party security authentication center, and the security query center selects a sequence preserving encryption algorithm to obtain a sequence preserving keyOrder-preserving key->The same key is shared for symmetric key, namely encryption and decryption. The security inquiry center determines the number n of the owners of the key fragments, namely tax electric nodes and the threshold value k, and adopts a Shamir threshold secret sharing algorithm to split the order-preserving keyObtaining n key slices->And each key fragment is respectively sent to a corresponding holder, and each tax node receives and stores one corresponding key fragment.
Wherein, a Shamir threshold secret sharing algorithm is adopted to split the order-preserving secret keyThe process of obtaining n key slices comprises the following steps:
step 1: taking the number of k-1 randomly in the finite field of 1 to p, and recording as，/>，…，/>Taking the coefficient as a coefficient of a non-constant term of a k-1 degree polynomial f (x);
step 2: building polynomials as...+/>；
Step 3: n holders are noted asHolder->Obtain subkey +.>。
And step S103, carrying out joint encryption on tax data fusion indexes according to the key fragments to obtain tax ciphertext.
Specifically, according to the principle of the Shamir threshold secret sharing algorithm, each tax node needs to obtain at least k key fragments when wanting to obtain the order-preserving key, namely each tax node needs to jointly encrypt tax data fusion indexes at least in combination with other k-1 tax nodes to obtain tax ciphertext.
Step S104, inquiring from the tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval.
Specifically, the query interval is a query condition directly input to the tax node by a user so as to query local data of the tax node; or query conditions input to the security query center to query the data stored by all tax nodes. In the former case, the local tax node encrypts the query interval based on the key fragment in combination with other tax nodes, and then compares the query interval ciphertext with the tax ciphertext to obtain a ciphertext data set, wherein the ciphertext data set obtained by query is the tax ciphertext located in the query interval. In the latter case, the security query center encrypts the query interval in order and then sends the encrypted query interval to each tax node, each tax node compares the encrypted query interval with each stored tax ciphertext to obtain a local ciphertext data set located in the query interval, and then sends the ciphertext data set to the security query center, and the security query center integrates the received ciphertext data set.
And step S105, performing joint decryption on the ciphertext data set according to the key fragments to obtain a query result.
Specifically, when a user directly inquires local data from the tax node, the tax node needs to jointly decrypt the ciphertext data set by combining other k-1 tax nodes to obtain an inquiry result. When a user inputs a query condition to the security query center, the tax node sends the key fragments and the ciphertext data set to the security query center, and the security query center decrypts the ciphertext data set according to the received key fragments to obtain a query result.
The user can know tax electric data fusion indexes of each time and space region through the query result, and the economic development condition can be objectively analyzed through the tax electric data fusion indexes calculated by combining tax data and electric power data.
According to the tax data safety fusion method, tax data and electric power data are combined to calculate tax data fusion indexes, key fragments obtained by dividing order-preserving keys according to a threshold secret sharing algorithm are received by a safety query center, the tax data fusion indexes are encrypted in a combined mode according to the key fragments to obtain tax ciphertexts, a ciphertext data set positioned in the query interval is queried from the tax ciphertexts based on the received query interval, the ciphertext data set is decrypted in a combined mode according to the key fragments to obtain query results, the economic development condition can be analyzed through querying the tax data fusion indexes, a plurality of tax nodes can encrypt and decrypt the tax data fusion indexes through the key fragments obtained by dividing the order-preserving keys based on a threshold secret sharing algorithm, the order-preserving keys can be obtained through the key fragments, therefore, each tax node can reconstruct the order-preserving keys only through the key fragments sent by other tax nodes, key safety is guaranteed, and as the ciphertext is queried only when the tax data fusion indexes are queried through encryption and decryption of the order-preserving keys, and then the query results can be decrypted, and all the tax data safety fusion indexes are not required.
In some alternative embodiments, in step S101, calculating tax data fusion metrics in combination with tax data and power data includes:
step S1011, calculating tax electric energy efficiency index, electricity consumption index and tax economic index by combining tax data and electric power data, wherein the calculation formula of the tax electric energy efficiency index is as follows:
in the method, in the process of the invention,represents tax electric energy efficiency index->Indicating tax electricity consumption in the period of time, +.>Representing the electricity consumption of the electric power in the period;
the calculation formula of the electricity consumption index is as follows:
in the method, in the process of the invention,indicating the power consumption index->、/>Representing the correspondingWeight coefficient->Indicating the number of users in the current period of power,/-, and>representing the number of power synchronous users, ">Representing the synchronous electricity consumption of the electric power;
the calculation formula of the tax economic index is as follows:
in the method, in the process of the invention,indicating tax economy index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the tax period>Representing tax contemporaneous user number,/->Indicating tax contemporaneous electricity consumption.
Step S1012, multiplying the tax electric energy efficiency index, the electric energy consumption index and the tax economic index by the corresponding weight coefficients to obtain a tax electric data fusion index, wherein the calculation formula of the tax electric data fusion index is as follows:
in the method, in the process of the invention,indicating tax electric data fusion index->、/>、/>Representing the corresponding weight coefficients.
Specifically, tax electrical energy efficiency indexFor analyzing economic benefit brought by unit energy consumption and power consumption indexBe used for analyzing social electricity energy consumption condition, tax economic index +.>The tax data fusion method is used for analyzing social tax conditions, and by combining tax data and electric power data to calculate tax electric energy efficiency indexes, electric energy consumption indexes, tax economic indexes, tax electric data fusion indexes and other indexes, the data barriers of each other are opened, the pain point problem existing in single data is solved, and the tax electric data fusion indexes have important significance in the aspects of accurate construction of service departments, quality improvement and efficiency enhancement of enterprises and the like.
Based on tax electric energy efficiency indexElectric consumption index->Tax economic index->Comprehensively calculated tax electric data fusion index +.>The method can analyze economic conditions by integrating tax and electricity consumption conditions, can construct a tax-electricity data fusion index multidimensional analysis model from multiple dimensions of time, area, industry and the like, and realizes multidimensional analysis for seeing economy by combining electric tax through different time scales of the year, quarter, month and the like.
In some alternative embodiments, in step S1011, tax electrical energy efficiency, electricity consumption, and tax economy are calculated in combination with tax data and power data, comprising:
And a step a1, generating a public-private key pair based on an approximate calculation homomorphic encryption algorithm, wherein the public-private key pair comprises a public key and a private key.
Specifically, a power N of 2 is selected, and a particular modulus P is definedSo that N and->Satisfy security level->Q is the scale of L-layer modulus, +.>Is a divisor of Q, L is ciphertext level, < >>For the defined value of the base at layer L, and (2)>For the security level parameter a private key-dependent distribution is selected +.>An error distribution->Then calculate the public private key pair +.>The calculation process is as follows:
step 1: instantiation ofAnd->；
Step 2: setting a private key；
Step 3: computing public keysWherein->。
Wherein,,representing a distribution related to the private key, +.>Indicating compliance->Distributed sample, < >>Representing an error distribution->Indicating compliance->Distributed sample, < >>Represents a private key->Represents the public key +_>Representing plaintext space,/->Representation ofA sample of space.
And a step a2, homomorphic encryption is carried out on the tax data and the electric power data according to the public key to obtain a tax data ciphertext and an electric power data ciphertext.
If the tax electric node is the electric power end equipment, the tax electric node receives tax data ciphertext sent by the tax end node, encrypts self electric power data and exchanges the self encrypted electric power data ciphertext to the corresponding tax end node, and the tax electric node encrypts the tax data or the electric power data as follows:
Selecting a random distributionUsed as encryption, plaintext->Generate->And->Constructing ciphertext->。
Wherein,,representing plaintext space, plaintext->，/>Representing an error distribution->And->Indicating compliance->Distributed sample, ++>Representing a random distribution->Indicating compliance->Distributed sample, < >>Representing ciphertext.
And a step a3, performing ciphertext fusion calculation by combining the tax data ciphertext and the electric power data ciphertext based on the corresponding calculation formula to obtain the tax electric energy efficiency index, the electric energy consumption index and the tax economic index.
In calculating tax electric energy efficiency indexElectric consumption index->Tax economic index->Tax electric data fusion index>When indexes are equal, the multiplication operation and the addition operation are used, so that three operators of ciphertext addition, ciphertext and plaintext multiplication and ciphertext multiplication are needed to be applied in ciphertext calculation, ciphertext statistics calculation logic is constructed through the three operators to perform ciphertext fusion calculation, and tax electric energy efficiency indexes, electric energy consumption indexes and tax are obtainedThe calculation formulas of the economic index and the three operators are as follows:
wherein,,representing plaintext space,/->Representing ciphertext space, plaintext->Two ciphertexts->，Representing ciphertext sum->Representing ciphertext and plaintext multiplication- >Representing ciphertext and ciphertext multiplication->Representing the auxiliary key->、/>And->Representing ciphertext->And->Intermediate value of>Representing rounding.
Based on ciphertext fusion calculation, the ciphertext of the tax electric energy efficiency index, the electricity consumption index and the tax economic index is obtained, the ciphertext of the tax electric data fusion index is calculated according to a calculation formula of the tax electric data fusion index, and then the ciphertext is decrypted through a private key, so that the decrypted tax electric data fusion index is obtained.
In the ciphertext operation, the ciphertext fusion calculation of the tax data is realized by utilizing ciphertext addition, ciphertext multiplication and ciphertext multiplication of an approximate calculation homomorphic encryption algorithm and ciphertext multiplication and plaintext multiplication, the encryption calculation result is decrypted through a private key, and the data confidentiality of the multi-main-body tax data is enhanced by mutually restricting each encryption and decryption party. And performing homomorphic encryption on tax data and electric power data through an approximate calculation homomorphic encryption algorithm, and performing ciphertext fusion calculation based on ciphertext, wherein each tax node only receives the ciphertext of data sent by other tax nodes and cannot know the plaintext, so that the data security of each tax node is ensured when tax data fusion indexes are calculated.
In some alternative embodiments, step S103, performing joint encryption on the tax data fusion index according to the key fragment to obtain the tax ciphertext includes:
Step S1031, based on the threshold value of the threshold secret sharing algorithm, requests to obtain key fragments of other tax nodes.
The threshold value of the threshold secret sharing algorithm is k, and the tax node needs to encrypt the tax data fusion index with the assistance of k key fragments, so that the tax node needs to initiate a request to other k-1 tax nodes to obtain the corresponding key fragments. And after other tax nodes agree to the encryption request, returning the own key fragments to the tax node which initiates the request.
Step S1032, obtaining the order-preserving key according to the key fragments of the self and the key fragments of other tax nodes.
Specifically, the calculation formula for recovering the order-preserving key through the k key fragments is as follows:
wherein,,representing an order-preserving key,/->Representing the ith key fragment.
And step S1033, encrypting the tax data fusion index based on the order-preserving key to obtain a tax ciphertext.
It can be understood that after the order-preserving key is recovered, the tax data fusion index is encrypted based on the order-preserving key to obtain the tax ciphertext. Illustratively, the process of encrypting the hydropower integration index x and outputting the electric ciphertext y by the tax electric node j with the assistance of k key fragments is expressed as follows:
And recovering the order-preserving key by requesting to acquire the key fragments of other tax nodes, and acquiring the key fragments of other tax nodes when encrypting data, thereby increasing the security of the key.
In some optional embodiments, step S104, querying, from the tax ciphertext, a ciphertext data set located in the query interval based on the received query interval, includes:
step S1041, sorting the local tax ciphertext based on the sorting algorithm of the equivalent data merging to obtain the local sorted tax ciphertext.
Specifically, the sorting algorithm based on equivalent data merging utilizes the dividing method idea to divide the tax-electricity ciphertext combination sequence into two parts under each round, then recursively sorts the left parts, recursively sorts the right parts, and realizes the efficient sorting of the tax-electricity ciphertext through multiple comparisons and exchanges.
Step S1042, inquiring from the locally ordered tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval.
Specifically, the order-preserving encryption ciphertext has ordering property, the inquiry interval ciphertext is obtained by carrying out order-preserving encryption on the inquiry interval, and the inquiry interval ciphertext is compared with the ordered tax ciphertext, so that the ciphertext data set positioned in the inquiry interval can be inquired.
The quick sorting of tax ciphertext is realized through the sorting algorithm based on equivalent data merging, and the stability and the efficiency of quick sorting and searching are improved.
In some alternative embodiments, step S105, performing joint decryption on the ciphertext data set according to the key fragment to obtain a query result, includes:
and b1, requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm.
And b2, calculating to obtain the order-preserving key according to the key fragments of the self and the key fragments of other tax nodes.
And b3, decrypting the ciphertext data set based on the order-preserving key to obtain a query result.
Specifically, the embodiment is used in the case that the user directly queries the tax node for local data. The threshold value of the threshold secret sharing algorithm is k, and the tax node needs to encrypt the tax data fusion index with the assistance of k key fragments, so that the tax node needs to initiate a request to other k-1 tax nodes to obtain the corresponding key fragments. And after other tax nodes agree to the encryption request, returning the key fragment to the tax node which initiates the request. After k key fragments are obtained, the calculation formula for recovering the order-preserving key is as follows:
After obtaining the order-preserving key, decrypting the ciphertext data set by the order-preserving key to obtain a query result, wherein the formula is as follows:
wherein,,representing an order-preserving key,/->Represents the ith key slice, +.>、/>Representing ciphertext data set and query result, respectively, +.>Representing the modulus.
And obtaining the key fragment decryption ciphertext data set of other tax nodes by request to realize local data query.
In some alternative embodiments, step S105, performing joint decryption on the ciphertext data set according to the key fragment to obtain a query result, includes:
and step c1, sending the key fragments and the ciphertext data set to a security query center.
And c2, carrying out joint sorting on the ciphertext data sets sent by the received tax nodes through a sorting algorithm based on equivalent data merging by the security query center, and carrying out joint decryption on the jointly sorted ciphertext data sets through the security query center and combining key fragments sent by other tax nodes to obtain a query result.
In particular, the embodiment is applicable to a scenario in which data of all tax nodes is queried from a security center.
The method comprises the steps that a user inputs query conditions to a security query center, the security query center encrypts the query conditions and then sends the query conditions to each tax node, each tax node compares the encrypted query interval with each sorted tax ciphertext to obtain a local ciphertext data set positioned in the query interval, then the ciphertext data set and each key fragment are sent to the security query center, and the security query center performs joint sorting on the ciphertext data sets sent by each received tax node through an equivalent data merging-based sorting algorithm. The ciphertext data sets sent by each tax node are ordered before being sent to the security query center, the security query center needs to perform joint ordering again on the ciphertext data sets sent by each tax node based on an ordering algorithm of equivalent data merging, and the joint decryption is performed on the ciphertext data sets after joint ordering by combining key fragments sent by other tax nodes to obtain a query result, and the decryption process is the same as that in the embodiment. The query result output by the safety query center comprises data which is stored by each tax node and accords with the query interval, and the data of all tax nodes can be integrally queried. The security query center recovers the order-preserving key and the decryption process is as follows:
Wherein,,representing an order-preserving key,/->Represents the ith key slice, +.>、/>Respectively representing tax data fusion indexes, namely plaintext and tax ciphertext, < >>Representing the modulus.
And carrying out joint sequencing on the ciphertext data sets sent by the tax nodes through the security query center, and carrying out joint decryption on the jointly sequenced ciphertext data sets by combining key fragments sent by other tax nodes through the security query center to obtain a query result, so as to realize the query on the data of a plurality of tax nodes.
The implementation process of the tax electric data safety fusion method according to the embodiment of the invention is described below with reference to a specific application example.
The tax-electricity-saving node is assumed to comprise tax-saving end equipment A, power-saving end equipment B and tax-saving end equipment B for performing tax-electricity data safety fusion.
The specific implementation scheme is as follows:
(1) And according to tax data fusion service data space, the tax-saving end equipment A, the power-saving end equipment B and the tax-saving end equipment B locally extract service data fields from respective databases.
(2) Public and private key pair constructed based on approximate calculation homomorphic encryption algorithm CKS。
(3) Each party passes through the public key And encrypting the local data for ciphertext exchange.
(4) Calculating tax electric energy efficiency index based on three operators of ciphertext addition, ciphertext and plaintext multiplication and ciphertext multiplicationElectric consumption index->Tax economic index->。
(5) According to the tax data fusion service, homomorphic ciphertext aggregation operation is carried out, tax data statistics feature calculation is realized, and tax data fusion indexes are obtained。
(6) Selecting order-preserving encryption algorithm and obtaining order-preserving secret keySplitting order-preserving key using Shamir threshold secret sharing algorithm>Generate 4 key slices +.>。
(7) And each party obtains the tax ciphertext by utilizing the key fragment joint encryption tax data fusion index, and performs local sequencing storage based on a quick sequencing algorithm of equivalent data merging.
(8) According to the tax-electricity data ciphertext joint search requirement, namely the query interval, the distributed joint search of the tax-electricity ciphertext is realized by introducing equivalent data search merging measures before a quick ordering algorithm.
(9) By k key shares, the key is recoveredDecrypting the plaintext of the retrieved tax ciphertext to obtain a query result.
In another application scenario, a query interval can be sent to each tax node through a security query center, each tax node compares the encrypted query interval with the tax ciphertexts which are stored in sequence respectively to obtain a local ciphertext data set positioned in the query interval, then the ciphertext data set and the key fragments of each ciphertext data set are sent to the security query center, then the security query center carries out joint sequencing on the obtained ciphertext data set, and runs a multi-party data order-preserving encryption mechanism decryption algorithm in combination with each provincial tax level platform to obtain a query result.
The tax electric data safety fusion method of the embodiment of the invention takes into account the requirements of quick ordering of multiparty ciphertext and safety protection of data of all parties, introduces a threshold key technology and a sequence-preserving encryption technology into the tax electric data fusion service, constructs a (k, n) threshold encryption and decryption scheme by carrying out threshold key design on a sequence-preserving encryption key, and realizes that the sequence-preserving encryption algorithm is applied to scenes of multiparty encryption and decryption by jointly encrypting tax electric fusion data through k key fragments of the sequence-preserving key, thereby ensuring key safety when carrying out data fusion and inquiry.
Based on a ciphertext ordering scheme of rapid ordering, the efficient retrieval analysis of the large-scale ciphertext is realized by using a divide-and-conquer method.
In addition, the tax electric data safety fusion method of the embodiment of the invention calculates the tax electric energy efficiency index, the electric energy consumption index, the tax economic index, the tax electric data fusion index and other indexes by combining the tax data and the electric power data, opens up each other data barriers, solves the pain point problem of single data, and has important significance in the aspects of accurate construction of service departments, quality improvement and efficiency enhancement of enterprises and the like.
The embodiment also provides a tax electric node based on tax electric data safety fusion, which is used for realizing the embodiment and the preferred implementation mode, and the description is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The embodiment of the invention also provides a tax electric node based on tax electric data safety fusion, as shown in fig. 3, comprising:
the index calculation module 301 is configured to calculate a tax data fusion index by combining tax data and electric power data;
the key fragment receiving module 302 is configured to receive a key fragment obtained by the security query center by splitting the order-preserving key according to a threshold secret sharing algorithm;
the joint encryption module 303 is configured to perform joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext;
the query module 304 is configured to query from the tax ciphertext based on the received query interval to obtain a ciphertext data set located in the query interval;
and the joint decryption module 305 is configured to perform joint decryption on the ciphertext data set according to the key fragment to obtain a query result.
According to the tax node based on tax data safety fusion, tax data and electric power data are combined to calculate tax data fusion indexes, key fragments obtained by splitting order-preserving keys according to a threshold secret sharing algorithm are received by a safety query center, tax ciphertext is obtained by carrying out joint encryption on the tax data fusion indexes according to the key fragments, a ciphertext data set positioned in a query interval is obtained by querying the tax ciphertext based on the received query interval, a query result is obtained by carrying out joint decryption on the ciphertext data set according to the key fragments, economic development conditions can be analyzed by querying the tax data fusion indexes, a plurality of tax nodes can carry out encryption and decryption on the tax data fusion indexes by splitting the key fragments obtained by the order-preserving keys based on a threshold secret sharing algorithm, the order-preserving keys can be obtained by a plurality of key fragments, therefore, each tax node can reconstruct the order-preserving keys by the key fragments sent by other tax nodes, the key ciphertext is ensured to be safe, and the query result can be obtained by only carrying out encryption and decryption on the ciphertext when the tax data fusion indexes are queried, and the safety of the tax data can be ensured not to be decrypted.
In some alternative embodiments, the metric calculation module 301 includes:
the first calculation module is used for calculating tax electric energy efficiency indexes, electric energy consumption indexes and tax economic indexes by combining tax data and electric power data, and the calculation formula of the tax electric energy efficiency indexes is as follows:
in the method, in the process of the invention,represents tax electric energy efficiency index->Indicating tax electricity consumption in the period of time, +.>Representing the electricity consumption of the electric power in the period;
the calculation formula of the electricity consumption index is as follows:
in the method, in the process of the invention,indicating the power consumption index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the current period of power,/-, and>representing the number of power synchronous users, ">Representing the synchronous electricity consumption of the electric power;
the calculation formula of the tax economic index is as follows:
in the method, in the process of the invention,indicating tax economy index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the tax period>Representing tax contemporaneous user number,/->Representing tax contemporaneous electricity consumption;
the second calculation index module is used for multiplying the tax electric energy efficiency index, the electric energy consumption index and the tax economic index by the corresponding weight coefficients respectively to obtain a tax electric data fusion index, and the calculation formula of the tax electric data fusion index is as follows:
in the method, in the process of the invention,indicating tax electric data fusion index->、/>、/>Representing the corresponding weight coefficients.
In some alternative embodiments, the first computing module comprises:
the key construction module is used for generating a public-private key pair based on an approximate calculation homomorphic encryption algorithm, wherein the public-private key pair comprises a public key and a private key;
the homomorphic encryption module is used for homomorphic encryption of tax data and electric power data according to the public key to obtain tax data ciphertext and electric power data ciphertext;
and the third calculation module is used for carrying out ciphertext fusion calculation by combining the tax data ciphertext and the electric power data ciphertext based on the corresponding calculation formula to obtain the tax electric energy efficiency index, the electric energy consumption index and the tax economic index.
In some alternative embodiments, the joint encryption module 303 includes:
the first fragment acquisition module is used for requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm;
the first key reconstruction module is used for calculating to obtain a sequence-preserving key according to the key fragments of the first key reconstruction module and the key fragments of other tax nodes;
and the order-preserving encryption module is used for encrypting the tax data fusion index based on the order-preserving key to obtain the tax ciphertext.
In some alternative embodiments, the query module 304 includes:
the first ordering module is used for ordering the local tax ciphertext based on an ordering algorithm of equivalent data merging to obtain the local ordered tax ciphertext;
The interval comparison module is used for inquiring from the locally ordered tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval.
In some alternative embodiments, the joint decryption module 305 includes:
the second fragment acquisition module requests to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm;
the second key reconstruction module calculates and obtains a sequence-preserving key according to the key fragments of the second key reconstruction module and the key fragments of other tax nodes;
and the order-preserving decryption module is used for decrypting the ciphertext data set based on the order-preserving key to obtain a query result.
In some alternative embodiments, the joint decryption module 305 includes:
the sending module is used for sending the key fragments and the ciphertext data set to the security query center;
and the joint decryption module is used for joint ordering of the ciphertext data sets sent by the received tax nodes through an ordering algorithm based on equivalent data merging of the security query center, and joint decryption of the jointly ordered ciphertext data sets through the security query center and the key fragments sent by other tax nodes to obtain a query result.
Further functional descriptions of the above respective modules and units are the same as those of the above corresponding embodiments, and are not repeated here.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present invention, and as shown in fig. 4, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing 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 embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 4.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform a method for implementing the embodiments described above.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; 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 alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise 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.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. The tax electric data safety fusion method is applied to one tax electric node in a tax electric system, and the tax electric system comprises a plurality of tax electric nodes, and is characterized by comprising the following steps:
calculating tax-electricity data fusion indexes by combining tax data and electric power data;
receiving a key fragment obtained by the security query center according to a threshold secret sharing algorithm by splitting the order-preserving key;
performing joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext;
inquiring from the tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval;
and carrying out joint decryption on the ciphertext data set according to the key fragment to obtain a query result.
2. The method of claim 1, wherein the calculating tax data fusion metrics in combination with tax data and power data comprises:
the tax electric energy efficiency index, the electricity consumption index and the tax economic index are calculated by combining tax data and electric power data, and the calculation formula of the tax electric energy efficiency index is as follows:
In the method, in the process of the invention,represents tax electric energy efficiency index->Indicating tax electricity consumption in the period of time, +.>Representing the electricity consumption of the electric power in the period;
the calculation formula of the electricity consumption index is as follows:
in the method, in the process of the invention,indicating the power consumption index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the current period of power,/-, and>representing the number of power synchronous users, ">Representing the synchronous electricity consumption of the electric power;
the calculation formula of the tax economic index is as follows:
in the method, in the process of the invention,indicating tax economy index->、/>Representing the corresponding weight coefficient, +.>Indicating the number of users in the tax period>Representing tax contemporaneous user number,/->Representing tax contemporaneous electricity consumption;
multiplying the tax electric energy efficiency index, the electric energy consumption index and the tax economic index by corresponding weight coefficients respectively to obtain a tax electric data fusion index, wherein the calculation formula of the tax electric data fusion index is as follows:
in the method, in the process of the invention,indicating tax electric data fusion index->、/>、/>Representing the corresponding weight coefficients.
3. The method of claim 2, wherein the calculating tax electrical energy efficiency index, electricity consumption index, and tax economic index in combination with tax data and power data comprises:
generating a public-private key pair based on an approximate calculation homomorphic encryption algorithm, wherein the public-private key pair comprises a public key and a private key;
Homomorphic encryption is carried out on tax data and electric power data according to the public key to obtain tax data ciphertext and electric power data ciphertext;
and carrying out ciphertext fusion calculation by combining the tax data ciphertext and the electric power data ciphertext based on the corresponding calculation formula to obtain the tax electric energy efficiency index, the electric energy consumption index and the tax economic index.
4. The method of claim 1, wherein the performing joint encryption on the tax data fusion index according to the key shard to obtain a tax ciphertext comprises:
requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm;
obtaining a sequence-preserving key according to the key fragments of the self and the key fragments of other tax nodes;
and encrypting the tax data fusion index based on the order-preserving key to obtain a tax ciphertext.
5. The method according to claim 1, wherein the querying the tax ciphertext based on the received query interval to obtain a ciphertext data set located in the query interval from the tax ciphertext comprises:
sorting the local tax ciphertext based on the equivalent data merging sorting algorithm to obtain a local sorted tax ciphertext;
Inquiring from the locally ordered tax ciphertext based on the received inquiry interval to obtain a ciphertext data set positioned in the inquiry interval.
6. The method of claim 1, wherein the jointly decrypting the ciphertext data sets according to the key shards results in a query result, comprising:
requesting to acquire key fragments of other tax nodes based on a threshold value of a threshold secret sharing algorithm;
obtaining a sequence-preserving key according to the key fragments of the self and the key fragments of other tax nodes;
and decrypting the ciphertext data set based on the order-preserving key to obtain a query result.
7. The method of claim 1, wherein the jointly decrypting the ciphertext data sets according to the key shards results in a query result, comprising:
the key fragments and the ciphertext data set are sent to a security query center;
and carrying out joint sorting on the ciphertext data sets sent by each received tax node through a sorting algorithm based on equivalent data merging of the security query center, and carrying out joint decryption on the jointly sorted ciphertext data sets by combining the key fragments sent by other tax nodes through the security query center to obtain a query result.
8. Tax electric data safety fusion-based tax electric node is characterized by comprising:
the index calculation module is used for calculating tax data fusion indexes by combining tax data and electric power data;
the key fragment receiving module is used for receiving the key fragments obtained by the security inquiry center through splitting the order-preserving key according to the threshold secret sharing algorithm;
the joint encryption module is used for carrying out joint encryption on the tax data fusion index according to the key fragment to obtain a tax ciphertext;
the query module is used for querying from the tax ciphertext based on the received query interval to obtain a ciphertext data set positioned in the query interval;
and the joint decryption module is used for joint decrypting the ciphertext data set according to the key fragment to obtain a query result.
9. A computer device, comprising:
a memory and a processor, the memory and the processor are in communication connection, the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the tax data security fusion method according to any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the tax data security fusion method of any one of claims 1 to 7.
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