CN115906127A - Joint computing system and method for government-enterprise privacy protection - Google Patents
Joint computing system and method for government-enterprise privacy protection Download PDFInfo
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- CN115906127A CN115906127A CN202211604811.3A CN202211604811A CN115906127A CN 115906127 A CN115906127 A CN 115906127A CN 202211604811 A CN202211604811 A CN 202211604811A CN 115906127 A CN115906127 A CN 115906127A
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Abstract
The invention provides a joint computing system and a joint computing method for government-enterprise privacy protection, wherein the system comprises an application layer, a service layer, a data layer and an infrastructure layer; the application layer is used for realizing application functions of the government-enterprise users, including data uploading, database connection, query analysis and result downloading; the service layer comprises a data service middle station and a data middle station, the data middle station is provided with a homomorphic encryption computing unit, and a data middle station system of homomorphic encryption technology is constructed through the homomorphic encryption computing unit; the data layer comprises government and enterprise data and third party data, wherein the third party data comprises various industry standard data and internet data; the infrastructure layer is used for providing facilities required for guaranteeing the operation of the joint computing system, including network, storage and computation. The invention provides a processing framework for helping government departments to perform government and enterprise joint analysis, and helps the government and enterprise to guarantee the data security in the data joint analysis process.
Description
Technical Field
The invention relates to the technical field of security, in particular to a joint computing system and a joint computing method for government and enterprise privacy protection.
Background
The combined analysis of the government and the enterprise is to combine the relevant data of the government and the enterprise and surround the cooperation business of the government and the enterprise such as: the enterprise pollution-tax payment balance, regional development-energy consumption and the like develop a series of index researches, strengthen the risk control and the overall situation grasp of government departments, and exert the value of enterprise data in the aspect of serving the national governance capability modernization.
With the continuous improvement of the informatization level of the government and enterprise departments, the exploration and the application of data elements are more and more urgent, but with the coming-out of policies such as the data security law, the network security law and the like, the data circulation security between the government and the enterprise becomes a barrier for hindering the data sharing application, the traditional data sharing and exchanging mechanism only can guarantee the security of the data in the retransmission process, the security of the data in the calculating process cannot be guaranteed, meanwhile, the data sharing and exchanging of the government and the enterprise lacks of credible security calculating schemes of both parties, and an effective framework does not guarantee the security of the whole process from the output of the data from an interface to the feedback of results.
Disclosure of Invention
In view of this, the invention provides a joint computing system and method for government-enterprise privacy protection, which take effective interaction and privacy protection into consideration, so as to better realize data sharing and joint analysis of government-enterprise and improve the quality and efficiency of digital transformation of government-enterprise.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a joint computing system for government and enterprise privacy protection comprises an application layer, a service layer, a data layer and an infrastructure layer;
the application layer is used for realizing application functions of the government-enterprise users, and comprises data uploading, database connection, query analysis and result downloading;
the service layer comprises a data service center station and a data center station, the data center station is provided with a homomorphic encryption computing unit, and a homomorphic encryption technology data center station system is constructed through the homomorphic encryption computing unit;
the data layer comprises government and enterprise data and third party data, wherein the third party data comprises various industry standard data and internet data;
the infrastructure layer is used for providing facilities required for guaranteeing the operation of the joint computing system, including network, storage and computation.
Furthermore, the data layer uploads the government and enterprise data to the system in an excel uploading or JDBC link mode.
The invention also provides a joint calculation method for protecting the privacy of the government and the enterprise, which comprises the following steps:
step 1: receiving data of the government and enterprise sides through a data layer of the joint computing system, and preprocessing the data;
and 2, step: a sharing exchange platform is set up, and the interconnection and intercommunication of the two sides of the government and the enterprise are realized through a national electronic government affair outer network, so that the mutual trust access of the front systems of the two sides is realized;
and step 3: constructing a government-enterprise calculation index model;
and 4, step 4: carrying out data alignment on data of both the government and the enterprise;
and 5: data encryption and delivery are carried out on data of both the government and the enterprise by using a self-adaptive CKKS algorithm;
step 6: performing joint calculation on data of both the government and the enterprise;
and 7: and carrying out security verification on the whole joint calculation process of the government and enterprise data.
Further, in step 1, the step of preprocessing the data includes:
step 101: checking the data filling rate, and if the data filling rate is lower than 50%, removing the type of data from the data of the two parties;
step 102: checking the data quality, removing the missing core field from the data of both parties, and processing the non-core field as follows: (1) taking an average value according to all data; (2) automatically filling according to the time-to-time ratio and the ring ratio; (3) filling in a fixed value; (4) predicting the position value by adopting a general LSTM time sequence algorithm;
step 103: checking whether the field data is null or 0 if the field data is used as a dividend in model calculation, filling if the field data is null, and throwing error exception if the field data is 0;
step 104: and (4) checking the data system, automatically converting the data into 10-system data, and reserving decimal point 2-bit digits.
Furthermore, in the step 2, RPC remote procedure call is adopted for access between front-end computers of the government and the enterprise, so that data intercommunication between the two parties is realized.
Further, in the step 2, service nodes of both the government and the enterprise realize service communication by means of a front-end processor of a government external network.
Further, the step 4 includes the following steps:
step 401: acquiring government data and taking a social unified credit code as a unique identifier of an enterprise;
step 402: acquiring enterprise data and taking a social unified credit code of an enterprise as a unique identifier of the enterprise;
step 403: and the MD5 encrypts the social unified credit codes of the two parties and respectively imports the encrypted data and the enterprise information into a government side system and an enterprise side system.
Further, the step 5 specifically includes encrypting data by using an adaptive CKKS algorithm, and calculating first before calculation:
k＝max(max(2 k ,a i 2 ),),k＝1,2,3,...,i＝1,2,3,...
wherein a is a parameter of calculation participation of both the government and the enterprise, k is a value which is calculated to be the first number square larger than the maximum number of calculation participation, and after the maximum value k of calculation participation of both the government and the enterprise is obtained, the calculation is carried out by the following steps:
q＝2 2k
and obtaining a calculated modulus q, and then obtaining an initial decimal number and a ciphertext dimension participating in CKKS calculation according to q value change to perform encryption calculation.
Further, in step 6, performing joint calculation in a data sandbox of the government and enterprise server according to the adaptive CKKS algorithm, including:
step 601: initializing a public key and a private key by a government department, distributing the public key to an enterprise, performing encryption operation through the public key by using a self-adaptive CKKS algorithm, and performing decryption operation by using the private key;
step 602: according to a preset government and enterprise index calculation formula, generating an intermediate result by using a self data calculation index, encrypting by using a public key, and simultaneously transmitting the calculation formula of the required index, the encrypted intermediate result and the data catalog required to participate in calculation to an enterprise data sandbox;
step 603: the enterprise performs authorization verification according to a data directory which is transmitted from a government department and needs to participate in calculation, allows data to be used for index calculation, and an administrator of the enterprise department selects corresponding operation in the system, and clicks to pass the verification if the current index calculation is not abnormal after the verification; if the abnormality exists, the rejection needs to be clicked, and the rejection reason is filled in a system interface;
step 604: after the authorization is completed, the enterprise uses the authorization data, locally executes index calculation according to an index calculation formula transmitted by the government department and the encrypted intermediate result to obtain an encrypted calculation result, and transmits the encrypted calculation result back to the government department;
step 605: and after obtaining the encrypted calculation result of the government and enterprise index, the government decrypts the calculation result by using the private key to obtain a final combined analysis result, and repeats the steps 602 to 605 to complete the calculation of a plurality of analysis indexes and realize the government and enterprise combined calculation work.
Compared with the prior art, the joint computing system and the joint computing method for the government and enterprise privacy protection have the following advantages that:
1. the invention provides a processing architecture for helping government departments to perform government and enterprise joint analysis, helps the government and enterprise to guarantee the data security in the data joint analysis process, and simultaneously provides a security check rule of multi-party cooperation analysis;
2. a general government and enterprise data joint analysis flow based on optimized CKKS homomorphic encryption is provided. The processing flow helps the government to calculate various indexes and simultaneously meets the requirements of enterprise data safety and confidentiality.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a federated computing system architecture diagram for government-enterprise privacy protection in accordance with the present invention;
FIG. 2 is a flowchart of the steps of a federated computing method for government-enterprise privacy protection in accordance with the present invention;
FIG. 3 is a diagram of a shared switching platform according to the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
The present invention will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
As shown in FIG. 1, the invention provides a joint calculation method and system for government and enterprise privacy protection, which mainly comprises an application layer, a service layer, a data layer and an infrastructure layer. The application layer in the system is an interface operation layer facing to the government and enterprise users, and provides application functions of data uploading, database connection, query analysis, result downloading and the like, and the specific analysis mode is determined by a business scene. The service layer comprises a data service middle station and a data middle station, wherein the privacy calculation function of the data middle station adopts an optimized CKKS homomorphic encryption technology to carry out actual calculation, and finally a data middle station system forming the homomorphic encryption technology is constructed. The data layer contains government and enterprise data and third party data, and the government and enterprise data are uploaded to the system in an excel uploading or JDBC link mode, and the third party data comprise: various industry standard data, internet data, etc. The infrastructure layer provides necessary network, storage, calculation and other facilities for guaranteeing the operation of the joint analysis system, the data two sides provide application servers or cloud environment resources, the system is deployed on the basis, and a special network is built, wherein the special network is detailed in building a sharing exchange platform.
In technical implementation, the joint computing system is designed to comply with a' business back-end scheduling homomorphic encryption computing module, and index computation is carried out on sensitive government data and sensitive enterprise data in an encryption state. And after the index calculation is finished, the demander decrypts the encrypted result to obtain the final index value. In order to achieve the purpose, both sides need to deploy homomorphic encryption computing units, are provided with a service background module to schedule homomorphic encryption modules and manage services such as data access, and are provided with a front-end management interface to facilitate management work of an administrator, audit of an auditor for index calculation, and bring up a new tax index calculation task for an analyst.
The joint calculation method for the protection of the privacy of the government and the enterprise of the invention is shown in figure 2 and comprises
(1) Data pre-processing
Due to data quality problems such as missing data items, non-existing data, and the like, data preprocessing before importing is essential. The data loss rate of part of enterprises reaches 50%, and business personnel are required to carry out preprocessing operation on data of both parties according to the situation. The pretreatment steps are as follows:
1. and checking the data filling rate, and if the data filling rate is lower than 50%, removing the type of data from the data of the two parties.
2. And (4) checking the data quality, and removing the missing core fields (such as a unified social credit code, a taxpayer identification number and the like) from the data of the two parties. The non-core field has the following rules: (1) the average was taken over all data. (2) And automatically filling according to the time-to-volume ratio and the ring ratio. (3) A fixed value is filled in. (4) The position value is predicted using the general LSTM time series algorithm. The specific rule selection is dependent on the traffic scenario and is averaged by default.
3. And checking whether the value is null or 0 if the position of the dividend of the field data in the model calculation is not null, filling if the value is null, and throwing error exception if the value is 0.
4. And (4) checking the data system, automatically converting the data into 10-system data, and reserving 2-bit digits of decimal points.
(2) Building sharing exchange platform
A shared switching platform is built as shown in fig. 3. By means of the external network of the national electronic government affairs, the interconnection and intercommunication of the two sides of the government and the enterprise are realized, and the preposed systems of the two sides can mutually trust and access. RPC remote procedure call is adopted for access between the front-end processors of the two parties, and data intercommunication between the two parties is realized. The government affair inner network and the government affair outer network are connected through a NET mapping forwarding technology, so that bidirectional intercommunication between a business service node in the government affair inner network and a front-end processor of the government affair outer network is realized; the privacy calculation node, the user access node and the service node belong to the big data platform sub-modules of each government department and access each other through an HTTP (hyper text transport protocol).
Service nodes of both the government and the enterprise realize service communication by means of a government affair outer network front-end processor, and mainly use an RPC protocol for communication. The RPC protocol specifies that one host program in the internet is allowed to call another without programming this interaction process. It is emphasized in the RPC protocol that when a procedure calls a function or method in a procedure B, a is unaware of the specific implementation of the method in B. The RPC protocol is based on a distributed architecture, so the RPC has the advantage of being unique in a distributed project, and the RPC protocol is completed by adopting a GRPC framework in the invention.
(3) Constructing a political and enterprise calculation index model
According to the united calculation requirements of the government and the enterprise, data field information and field metadata of all the government and the enterprise are extracted, business personnel carry out theoretical construction of an index model, and system operation and maintenance personnel/algorithm personnel carry out auditing and inputting of the index model. For example, in the financial-insurance industry, index models are constructed by two parties of a bank-insurance company, and data such as insurance pricing, premium, client credit, client fund and the like are extracted to perform joint insurance application risk modeling. Or in the national grid-vehicle enterprise industry, the two parties provide information such as the position, the location and the idle state of the electric pile of the electric vehicle, and the optimal charging path planning model is carried out.
(4) Data alignment
In order to meet the data input requirements of the index models, data and corresponding data sources and fields depending on each index model need to be analyzed, the description of the government data information and the data information of a plurality of enterprises on the same enterprise is unified through data preprocessing, the ownership of each data is determined, and the steps of data import, encryption, release and the like are performed subsequently, so that the index model calculation is performed. The specific implementation method comprises the following steps:
1. government data is acquired and a social unified credit code is used as a unique identification of the enterprise.
2. And acquiring enterprise data and taking the social unified credit code of the enterprise as the unique identifier of the enterprise.
3. And encrypting the social unified credit codes of the two parties through the MD5, and respectively importing the encrypted data and the enterprise information into a government side system and an enterprise side system.
(5) Data encryption delivery of data of both government and enterprise sides by using self-adaptive CKKS algorithm
The invention provides a self-adaptive CKKS algorithm on the basis of the traditional CKKS, and the self-adaptive CKKS algorithm is firstly calculated before calculation:
k＝max(max(2 k ,a i 2 ) K =1,2,3,. I =1,2,3
Wherein a is a parameter of calculation participation of both the government and the enterprise, k is a value which is calculated to be the first number square larger than the maximum number of calculation participation, and after the maximum value k of calculation participation of both the government and the enterprise is obtained, the calculation is carried out by the following steps:
q＝2 2k formula two
The calculated modulus q is obtained. And after q is obtained, the initial decimal place and the ciphertext dimension participating in CKKS calculation can be obtained according to the q value change, and encryption calculation is carried out. The method not only ensures that the waste of computing resources caused by fixed parameters is avoided, but also ensures that the overflow of the plaintext encryption value caused by too low ciphertext modulus is avoided.
(6) Joint computing process
According to the self-adaptive CKKS algorithm, joint calculation is carried out in a data sandbox of the government and enterprise server, and the data sandbox is a local trusted software execution environment deployed by both the government and enterprise.
Step 1: public and private keys are initialized by government authorities and distributed to enterprises. And using an adaptive CKKS algorithm, carrying out encryption operation through a public key, and carrying out decryption operation by using a private key.
Step 2: and according to a preset government and enterprise index calculation formula, calculating indexes by using self data to generate an intermediate result, and encrypting by using a public key. Meanwhile, a calculation formula of the required index, an encrypted intermediate result and a data directory required to participate in calculation are transmitted to an enterprise data sandbox.
And step 3: the enterprise performs authorization and verification according to the data catalogue which is transmitted from the government department and needs to participate in calculation, and allows the data to be used for index calculation. An enterprise department administrator can select corresponding operation in the system, and if the current index calculation is not abnormal after the audit, the enterprise department administrator clicks to pass the audit; if the abnormality exists, the rejection needs to be clicked, and the reason of rejection is filled in the system interface.
And 4, step 4: after the authorization is completed, the enterprise uses the authorization data, performs index calculation locally according to an index calculation formula transmitted by the government department and the encrypted intermediate result to obtain an encrypted calculation result, and transmits the encrypted calculation result back to the government department.
And 5: and after the government obtains the encrypted calculation result of the government and enterprise index, the government decrypts the calculation result by using the private key to obtain a final combined analysis result. And (5) repeating the steps 2-5, so that the calculation of a plurality of analysis indexes can be completed, and the government-enterprise joint calculation work is realized.
The invention ensures that all data of all parties are encrypted in the whole calculation process of the government-enterprise joint calculation, so that the original data cannot be seen mutually, and only the calculation result can be obtained. On the premise of ensuring data safety, the data is fully utilized.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A federated computing system for government-enterprise privacy protection, characterized by: the system comprises an application layer, a service layer, a data layer and an infrastructure layer;
the application layer is used for realizing application functions of the government-enterprise users, and comprises data uploading, database connection, query analysis and result downloading;
the service layer comprises a data service center station and a data center station, the data center station is provided with a homomorphic encryption computing unit, and a homomorphic encryption technology data center station system is constructed through the homomorphic encryption computing unit;
the data layer comprises government and enterprise data and third party data, wherein the third party data comprises various industry standard data and internet data;
the infrastructure layer is used for providing facilities required for guaranteeing the operation of the joint computing system, and comprises a network, a storage layer and a computation layer.
2. A federated computing system for political-enterprise privacy protection as defined in claim 1, wherein: and the data layer uploads the government and enterprise data to the system in an excel uploading or JDBC link mode.
3. A joint calculation method for government-enterprise privacy protection is characterized by comprising the following steps: the method comprises the following steps:
step 1: receiving data of both the government and the enterprise through a data layer of the joint computing system, and preprocessing the data;
step 2: a sharing exchange platform is set up, network interconnection and intercommunication between two government and enterprise parties are realized through a national electronic government outer network, and mutual trust access of front systems of the two parties is realized;
and step 3: constructing a government-enterprise calculation index model;
and 4, step 4: carrying out data alignment on data of both the government and the enterprise;
and 5: data encryption and delivery are carried out on data of both the government and the enterprise by using a self-adaptive CKKS algorithm;
and 6: and performing joint calculation on the data of the government and the enterprise.
4. A joint calculation method for political-enterprise privacy protection according to claim 3, wherein: in step 1, the step of preprocessing the data includes:
step 101: checking the data filling rate, and if the data filling rate is lower than 50%, removing the type of data from the data of the two parties;
step 102: and (3) checking the data quality, removing the missing core fields from the data of the two parties, and processing the non-core fields as follows: (1) taking an average value according to all data; (2) automatically filling according to the time-to-time ratio and the ring ratio; (3) filling a fixed value; (4) predicting the position value by adopting a general LSTM time sequence algorithm;
step 103: checking whether the field data is null or 0 if the field data is used as a dividend in model calculation, filling if the field data is null, and throwing error exception if the field data is 0;
step 104: and (4) checking the data system, automatically converting the data into 10-system data, and reserving 2-bit digits of decimal points.
5. A joint calculation method for political-enterprise privacy protection according to claim 3, wherein: in the step 2, RPC remote procedure call is adopted for access between front-end computers of the government and the enterprise, so that data intercommunication between the two parties is realized.
6. A federated computing method for political-enterprise privacy protection as defined in claim 3, wherein: in the step 2, service nodes of both the government and the enterprise realize service communication by means of a front-end processor of a government external network.
7. A federated computing method for political-enterprise privacy protection as defined in claim 3, wherein: the step 4 comprises the following steps:
step 401: acquiring government data and taking a social unified credit code as a unique identifier of an enterprise;
step 402: acquiring enterprise data and taking a social unified credit code of an enterprise as a unique identifier of the enterprise;
step 403: and the MD5 encrypts the social unified credit codes of the two parties and respectively imports the encrypted data and the enterprise information into a government side system and an enterprise side system.
8. A federated computing method for political-enterprise privacy protection as defined in claim 3, wherein: the step 5 specifically includes encrypting data by using a self-adaptive CKKS algorithm, and calculating first before calculation:
k＝max(max(2 k ,a i 2 ),),k＝1,2,3,...,i＝1,2,3,...
wherein a is a parameter of calculation participation of both the government and the enterprise, k is a value which is calculated to be the first number square larger than the maximum number of calculation participation, and after the maximum value k of calculation participation of both the government and the enterprise is obtained, the calculation is carried out by the following steps:
q＝2 2k
and obtaining a calculated modulus q, obtaining an initial decimal digit and a ciphertext dimension participating in CKKS calculation according to the q value change after the q is obtained, and performing encryption calculation.
9. A joint calculation method for political-enterprise privacy protection according to claim 3, wherein: in step 6, performing joint calculation in a data sandbox of the government and enterprise server according to a self-adaptive CKKS algorithm, wherein the joint calculation comprises the following steps:
step 601: initializing a public key and a private key by a government department, distributing the public key to an enterprise, performing encryption operation through the public key by using a self-adaptive CKKS algorithm, and performing decryption operation by using the private key;
step 602: according to a preset government and enterprise index calculation formula, generating an intermediate result by using a self data calculation index, encrypting by using a public key, and simultaneously transmitting the calculation formula of the required index, the encrypted intermediate result and the data catalog required to participate in calculation to an enterprise data sandbox;
step 603: the enterprise performs authorization verification according to a data directory which is transmitted from a government department and needs to participate in calculation, allows data to be used for index calculation, and an administrator of the enterprise department selects corresponding operation in the system, and clicks to pass the verification if the current index calculation is not abnormal after the verification; if the abnormality exists, the rejection needs to be clicked, and the rejection reason is filled in a system interface;
step 604: after the authorization is completed, the enterprise uses the authorization data, locally executes index calculation according to an index calculation formula transmitted by a government department and an encrypted intermediate result to obtain an encrypted calculation result, and transmits the encrypted calculation result back to the government department;
step 605: and after obtaining the encrypted calculation result of the government and enterprise index, the government decrypts the calculation result by using the private key to obtain a final combined analysis result, and repeats the steps 602 to 605 to complete the calculation of a plurality of analysis indexes and realize the government and enterprise combined calculation work.
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| CN116226928A (en) * | 2023-05-09 | 2023-06-06 | 京东科技控股股份有限公司 | Combined computing method, device, equipment and medium for multiparty business privacy data |
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| CN116226928A (en) * | 2023-05-09 | 2023-06-06 | 京东科技控股股份有限公司 | Combined computing method, device, equipment and medium for multiparty business privacy data |
| CN116226928B (en) * | 2023-05-09 | 2024-04-16 | 京东科技控股股份有限公司 | Combined computing method, device, equipment and medium for multiparty business privacy data |
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