CN111125753A - Credit data determination method and device - Google Patents
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- CN111125753A CN111125753A CN201911253517.0A CN201911253517A CN111125753A CN 111125753 A CN111125753 A CN 111125753A CN 201911253517 A CN201911253517 A CN 201911253517A CN 111125753 A CN111125753 A CN 111125753A
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Abstract
The specification discloses a method and a device for determining credit data. The method comprises the following steps: sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users; receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder; carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user; and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user. The scheme can determine the comprehensive credit data of the user and does not reveal the personal privacy of the user.
Description
Technical Field
The present disclosure relates to the field of information security, and in particular, to a method and an apparatus for determining credit data.
Background
With the development of internet technology, users can access various internet platforms, service data of users performing service operations in the internet platforms may reflect credit of the users to a certain extent, and the service data of the users often relate to personal privacy.
Disclosure of Invention
In view of the above, the present specification provides a method and an apparatus for determining credit data.
Specifically, the description is realized by the following technical scheme:
a credit data determination method is applied to a credit data determiner and comprises the following steps:
sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users;
receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder;
carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
A credit data determination device applied to a credit data determination party comprises:
the system comprises a sending unit, a receiving unit and a sending unit, wherein the sending unit sends a private data query request to one or more data holders, and the data holders hold credit-related private data of a plurality of users;
the receiving unit is used for receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the private data held by the corresponding data holder;
the decryption unit is used for carrying out safe decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and the determining unit is used for determining the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user.
One embodiment of the present specification realizes that a determining party of credit data can send a private data query request to one or more data holding parties, the data holding parties receive the request and then securely encrypt the credit-related private data of a plurality of users and return the credit-related private data to the determining party, and the determining party can securely decrypt the encrypted private data to obtain the private data of a target user. Based on this, the determining party may determine the comprehensive credit data of the target user based on the private data of the target user from the data holder in combination with the local credit data of the target user. Based on the method, the comprehensive credit data of the target user can be determined on the premise of not revealing the privacy of the user.
Drawings
Fig. 1 is a flowchart illustrating a method for determining credit data according to an exemplary embodiment of the present disclosure.
Fig. 2 is a flowchart illustrating another method for determining credit data according to an exemplary embodiment of the present disclosure.
Fig. 3 is a schematic structural diagram of a determination apparatus for credit data according to an exemplary embodiment of the present specification.
Fig. 4 is a block diagram of a credit data determination apparatus according to an exemplary embodiment of the present specification.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the specification, as detailed in the appended claims.
The terminology used in the description herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the description. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, the first information may also be referred to as second information, and similarly, the second information may also be referred to as first information, without departing from the scope of the present specification. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
With the development of internet technology, users can access various internet platforms, and service data of service operations performed by users in some internet platforms may reflect credit of users to a certain extent. Taking a shared bicycle as an example, when a user uses the shared bicycle, the user can generate the bicycle borrowing and returning records of the user, and the records can reflect the credit condition of the user, for example, for the user with high bicycle returning rate, the credit of the user can be determined to be better; for users with low car return rate, the credit is determined to be poor.
The comprehensive credit condition of the user can be determined through credit-related service data generated by the user on different internet platforms, however, the credit-related service data often relates to the personal privacy of the user, and how to determine the comprehensive credit condition of the user on the premise of not revealing the privacy of the user becomes a problem to be solved urgently.
The specification provides a method and a device for determining credit data.
Fig. 1 is a flowchart illustrating a method for determining credit data according to an exemplary embodiment of the present disclosure.
The method for determining credit data may be applied to an electronic device having a processor and a memory, such as a server or a server cluster, and the specification is not limited thereto.
Referring to fig. 1, the method for determining credit data may include the following steps:
step 101, sending a private data query request to one or more data holders, said data holders holding credit related private data of a number of users.
And 102, receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder.
In this specification, the credit data determiner and the data holder may be internet platforms such as a shopping platform, a credit platform, a book borrowing platform, and the like, or social organizations such as schools, communities, enterprises, and the like, and this specification is not limited thereto.
In this specification, a party who determines the user comprehensive credit data may be referred to as a party who determines the credit data, and a party who provides the user private data to the party who determines may be referred to as a data holder.
In one example, the credit-related private data may be service data of a user performing service operations on various internet platforms, and the service data may reflect credit status of the user.
For example: for a shopping platform, the credit-related private data may be a return record for a user, which may include: information on whether the user returns goods on time, quality information of returned goods and the like; for a credit platform, the credit-related private data may be a debit and payment record of the user; for the payment platform, the credit-related private data can be records of water payment, electric charge payment and the like for the user; for the book borrowing platform, the credit related private data can be book borrowing and book returning records of the user.
The following table exemplarily shows credit-related private data of a user on a book borrowing platform:
| user' s | Book borrowing time | Book return time | Days of expiry |
| A | 2019.08.10 | 2019.09.10 | 0 |
| A | 2019.08.10 | 2019.12.13 | 20 |
| A | 2019.9.16 | 2019.12.03 | 3 |
In another example, the credit-related private data may also be credit ratings of users in various internet platforms or social organizations. The credit rating may be a credit score, credit rating, etc. of the user.
When determining the comprehensive credit data of the user, the credit data determining party may send a private data query request to one or more data holding parties, where the private data query request may carry identification information of the determining party. The identification information may be an ID, an IP address, a name, etc. of the determination party, which is not particularly limited in this specification.
In an example, when receiving the private data query request, the data holder may search for private data of all users held by the data holder, then perform secure encryption on the private data of all users to obtain encrypted private data, and return the encrypted private data to the determining party according to identification information of the determining party.
For example, if the credit data determiner is a school, the data holder is a shopping platform, and the school sends a private data query request to the shopping platform, where the request may include an IP address of the school: 192.168.0.1, the shopping platform can search the private data of all users held by the shopping platform after receiving the request, and the private data is encrypted safely to obtain encrypted private data, and then the encrypted private data is returned to the school according to the IP.
In another example, when receiving the private data query request, the data holder may search for private data of a user holding the private data corresponding to the identification information, perform secure encryption on the private data of the corresponding users to obtain encrypted private data, and return the encrypted private data to the determining party according to the identification information of the determining party.
For example, if the party determined to be credit data is a school, the data holder is a shopping platform. The school sends a private data query request to the shopping platform, and the request contains the IP address of the school: 192.168.0.1. after receiving the request, the shopping platform can search the private data of the user corresponding to the IP address, such as the private data of the school student, then can perform secure encryption on the private data to obtain encrypted private data, and then returns the encrypted private data to the school according to the IP address.
In this specification, the secure encryption may be secure encryption based on multi-party secure computation, or secure encryption based on two-party secure computation.
For the two-party security calculation, only one data holder and one determining party are provided, and the data holder carries out security encryption on the private data and then returns the private data to the determining party.
For multi-party secure computing, multiple data holders may securely encrypt their own private data and return the encrypted private data to the determining party.
For example, if the target user of the determination party is zhang-three, the first data holder may return the credit-related private data of zhang-three and lie-four to the determination party, and the second data holder may return the credit-related private data of zhang-three and wang-five to the determination party, the determination party may obtain the private data of zhang-three from the private data returned by the first data holder and the second data holder, respectively, and determine the comprehensive credit data of zhang-three by combining the local credit data of zhang-three.
The following describes in detail the process of performing secure encryption based on two-party secure computation:
in this example, the encrypted private data may be private data encrypted by Garbled Circuit (hereinafter, GC encryption). For the data holder and the determining party, the GC encryption only reveals the calculation result and does not reveal the input value and the intermediate value, so as to protect the privacy of private data.
In one example, the data holder and the determiner may agree in advance with a common function, and the common function may be a summation function, a maximum calculation function, or the like, which is not particularly limited in this specification.
When it is determined that a private data query request is initiated by a data holder, the public function may be carried in the data query request, or the public function may be sent separately.
After the data holder acquires the public function, the GC encryption can be executed to obtain encrypted private data of a plurality of users, and the specific process is as follows:
1. converting the common function to an equivalent logic circuit.
The common function is represented in computer language by a circuit composed of an adder, a multiplier, a shifter, a selector, and the like, which can be represented by two logic gates, an and gate and an xor gate, and thus can be converted into a logic circuit. In practical applications, a manual compiler or a circuit compiler may be used to convert the common function into a logic circuit.
2. And inputting the input parameters into the logic circuit to obtain the circuit information of the logic circuit.
And the data holder inputs the private data of a plurality of users as input parameters into the logic circuit to obtain the circuit information of the logic circuit, and the circuit information is used as the encrypted private data.
And after the data holder completes GC encryption, the encrypted private data is sent to the determining party.
In one example, the data holder may send the encrypted private data to the determining party.
In another example, the data holder may also send the encrypted private data and the logic circuit to the determiner.
And 103, carrying out safe decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user.
In this specification, the secure decryption may be a secure decryption based on a two-party secure computation.
The following describes in detail the process of secure decryption based on two-party secure computation: and the determining party executes an Oblivious Transfer algorithm (OT algorithm) to acquire the private data of the target user after the encryption of the GC from the plurality of users.
In this specification, the OT algorithm can implement: the data holding direction determining party sends N pieces of private data, and the determining party acquires the private data of the target user from the N pieces of private data, but the data holding party cannot know which target users' private data in the N pieces of private data are received by the determining party, and the determining party cannot acquire the private data of other users in the N pieces of private data except for the target user.
In this example, after the private data encrypted by the GC of the target user is obtained, the private data of the target user can be further obtained through Garbled Circuit decryption (hereinafter, GC decryption).
In practical application, the determining party obtains the private data of the target user after the GC encryption, the private data after the GC encryption can be circuit information obtained by inputting the private data of the target user into the logic circuit, and then the determining party can perform the GC decryption based on the circuit information and the logic circuit to obtain the private data of the target user after the GC decryption.
And 104, determining comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user.
In this specification, the local credit data of the target user is credit-related data of the target user local to the determining party.
For example, if the determiner is a campus, the local credit data of the target user may be book borrowing and returning records of the target student in a library; consumption records of target students in the canteens; violation records of the target student in the campus, and the like.
Of course, if the determining party is the internet platform or other social organization in step 101 and step 102, the local credit related data may also be the return records of the shopping platform, the borrowing records of the credit platform, and the like, which are not described herein again.
The local credit data of the target user may be a piece of credit-related data, or may be a plurality of pieces of credit-related data of the target user within a preset statistical period.
For example, if the determiner is a campus and the statistical period is determined to be a school year, the local credit data of the target user may be determined as a record of the overdue borrowing and returning of the target student within the last school year.
In this specification, the comprehensive credit data of the target user may be determined based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
In practical application, the one or more pieces of private data of the target user obtained based on the secure decryption and the local credit data of the target user may be input into a preset function to obtain the comprehensive credit data of the target user.
In one example, the preset function may be the common function in step 102, and the common function may be a summation function, a maximum calculation function, a minimum calculation function, or the like.
If the preset function is a maximum value calculation function, the determining party can calculate the maximum value of one or more pieces of private data of the target user and local credit data of the target user, which are obtained based on the security decryption, so as to obtain comprehensive credit data of the target user.
For example, if the private data of the target user obtained based on the security decryption is the credit score of the target student on a credit platform, and the local credit data of the target user is the credit score of the target student on a campus, the credit score of the target student on the credit platform and the credit score of the target student on the campus may be maximized, and the result with higher credit score is used as the comprehensive credit data of the target student.
In other examples, the preset function may also be other functions, and the present specification does not specifically limit this.
In practical applications, the credit rating of the target user may be further performed based on the private data of the target user and the local credit data of the target user returned by the multiple data parties, so as to determine the comprehensive credit data of the target user.
For example, the determiner is a campus, the data holder is a plurality of internet platforms, and the determining may be: a shopping platform, a credit platform, a book borrowing platform.
And the campus safely decrypts the safely encrypted private data of the target students returned by the Internet platforms to obtain credit scores of the target students by the Internet platforms. For example, the credit score of the targeted student on the shopping platform is 80 points; credit score at credit platform 90 points; and if the credit score of the book borrowing platform is 70 scores and the local credit score of the target student in the campus is 85 scores, the campus can perform weighted average calculation on the four scores, and the four scores are multiplied by a preset weighted average coefficient and then added to obtain a comprehensive credit score of the target student.
In other examples, after the private data of the target user returned by the data party is obtained, the comprehensive credit data of the target user may also be determined in other manners, which is not limited in this specification.
As can be seen from the above description, in an embodiment of the present specification, a determining party of credit data may send a private data query request to one or more data holders, and securely decrypt encrypted private data returned by the one or more data holders to obtain private data of a target user required by the determining party. Further, the determiner may determine the aggregate credit data for a target user based on private data from the target user from one or more data holders in conjunction with local credit data for the target user.
According to the method, the credit-related private data of the target users of the multiple data holders can be acquired, and the comprehensive credit data of the target users can be determined. And the private data is safely encrypted during transmission, so that the privacy of the user cannot be revealed, and the personal information safety of the user is ensured.
The method for determining credit data in the present specification will be described with reference to a specific example.
The embodiment is established in a scene of the credit system construction of students in colleges and universities, wherein the determining party is a certain school, and the data holding party is a certain credit platform.
The school has released the payment mode of "give after getting used first" in campus dining room, and the student can have a meal first in the dining room, pays after having a meal. However, for some students with poor credit, there may be a case where no payment is made after a meal. On this basis, it is necessary to take different measures for students with different credit statuses. However, in the student activity records performed by students in the campus, there are few activity records that can be used for evaluating the credit status of the students, and the credit status of the students cannot be fully reflected. In this embodiment, the school may obtain credit-related data of students on a credit platform to determine the comprehensive credit status of the students.
Referring to fig. 2, fig. 2 is a flowchart illustrating another credit data determination method according to an exemplary embodiment of the present disclosure.
The credit data determination method may be applied to the servers of the school and the credit platform.
In this embodiment, the request includes identification information of a school, the public function is a function for calculating the number of overdue repayment times, and the public function may be carried in the query request
At step 202, the credit platform converts the common function into an equivalent logic circuit.
In this embodiment, the common function may be converted into an equivalent logic circuit by a circuit compiler Frutta.
In this embodiment, if the credit platform determines that the requester is a school based on the identification information, the equivalent logic circuit may input the student private data corresponding to the school in the credit platform.
For example, the credit platform determines that students corresponding to the school are: the student A, B first obtains the credit-related private data of the student A, B in the platform and inputs the obtained private data into the function for calculating the number of overdue repayment.
The following table exemplarily shows credit-related private data of a student A, B determined by a credit platform:
| user identification | Time of borrowing | Amount of money to be borrowed | Repayment time | Number of overdue repayment days |
| A | 2019.05.06 | 1000 | 2019.08.06 | 0 |
| A | 2019.05.06 | 500 | 2019.08.16 | 10 |
| A | 2019.08.13 | 2500 | 2019.11.15 | 2 |
| B | 2019.03.03 | 2000 | 2019.04.08 | 0 |
And step 204, the credit platform sends the plurality of student private data encrypted by the GC to a school.
In step 205, the school executes OT algorithm to obtain private data of the target student after GC encryption from the plurality of students.
In this example, if the target student determined by the school is student a, the school may execute an OT algorithm to obtain private data of the student a encrypted by the GC from the plurality of students.
And after the school performs GC decryption on the private data of the student A after the GC encryption, the number of the overdue repayment of the student A on the credit platform can be obtained. From the above table, the number of overdue repayment of student a on the credit platform is 2.
In this embodiment, the local credit data for student a may be the credit score for student a on the campus. And combining the overdue repayment times of the student A returned by the credit platform, and deducting 5 points for the credit score of the student A if the overdue repayment times are once, so as to calculate the comprehensive credit score of the student A.
For example, if student A has a credit score of 60 points on the campus. According to the above table, if the student A has two overdue repayment, the comprehensive credit score of the student A is: 60-5-50 points.
As can be seen from the above description, in another embodiment of the present specification, a school can obtain credit related data of students on other platforms through a multiparty security algorithm, and determine a comprehensive credit score of the student by combining the local credit related data of the student, without revealing the individual privacy of the student in the whole process.
After the school acquires the comprehensive credit scores of the students, different implementation modes of sharing before paying can be adopted for different students according to different credit scores of different students. For example, the school may allow students with higher composite credit scores to enjoy a greater number of "pay-after-share" payment methods, and allow students with higher composite credit scores to enjoy a lesser number of "pay-after-share" payment methods, so as to take different measures for students with different credit scores.
In correspondence with the foregoing embodiments of the method for determining credit data, the present specification also provides embodiments of a device for determining credit data.
The embodiment of the credit data determination apparatus in the present specification can be applied to a server. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, as a logical device, the device is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory for operation through the processor of the server where the device is located. From a hardware aspect, as shown in fig. 3, a hardware structure diagram of a server where a device for determining credit data is located in the present specification is shown, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 3, the server where the device is located in the embodiment may also include other hardware according to an actual function of the server, which is not described again.
Fig. 4 is a block diagram of a credit data determination apparatus according to an exemplary embodiment of the present specification.
Referring to fig. 4, the credit data determining apparatus 600 may be applied in the server shown in fig. 3, and includes: a sending unit 610, a receiving unit 620, a decrypting unit 630 and a determining unit 640.
A sending unit 610, sending a private data query request to one or more data holders, the data holders holding credit related private data of a number of users.
The receiving unit 620 receives encrypted private data returned by the one or more data holders, where the encrypted private data is obtained by performing secure encryption on the held private data by the corresponding data holder.
The decryption unit 630 performs secure decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user.
The determining unit 640 determines the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user.
Optionally, the private data query request carries identification information of the determining party, and the encrypted private data is obtained by performing secure encryption on the private data of the user corresponding to the identification information and held by the corresponding data holding party.
Optionally, the secure encryption is obfuscated circuit encryption, and the secure decryption includes:
executing an inadvertent transmission algorithm, and acquiring private data of the target user after being encrypted by the garbled circuit from encrypted private data returned by the data holder;
and carrying out obfuscation circuit decryption on the private data of the target user after being encrypted by the obfuscation circuit to obtain the private data of the target user.
Optionally, the determining unit 640:
and inputting the one or more pieces of private data of the target user obtained based on the security decryption and the local credit data of the target user into a preset function to obtain the comprehensive credit data of the target user.
Optionally, the target user is a student, and the local credit data includes one or more of the following:
library book borrowing records, canteen consumption records and campus violation records.
Optionally, the credit-related private data comprises one or more of:
consumption records, payment records, loan records and loan amounts.
The implementation process of the functions and actions of each unit in the above device is specifically described in the implementation process of the corresponding step in the above method, and is not described herein again.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution in the specification. One of ordinary skill in the art can understand and implement it without inventive effort.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
In correspondence with an embodiment of the foregoing method for determining credit data, the present specification also provides a device for determining credit data, the device including: a processor and a memory for storing machine executable instructions. Wherein the processor and the memory are typically interconnected by means of an internal bus. In other possible implementations, the device may also include an external interface to enable communication with other devices or components.
In this embodiment, the processor is caused to:
sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users;
receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder;
carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
Optionally, the private data query request carries identification information of the determining party, and the encrypted private data is obtained by performing secure encryption on the private data of the user corresponding to the identification information and held by the corresponding data holding party.
Optionally, the secure encryption is a garbled circuit encryption, and upon the secure decryption, the processor is caused to:
executing an inadvertent transmission algorithm, and acquiring private data of the target user after being encrypted by the garbled circuit from encrypted private data returned by the data holder;
and carrying out obfuscation circuit decryption on the private data of the target user after being encrypted by the obfuscation circuit to obtain the private data of the target user.
Optionally, when determining the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user, the processor is caused to:
and inputting the one or more pieces of private data of the target user obtained based on the security decryption and the local credit data of the target user into a preset function to obtain the comprehensive credit data of the target user.
Optionally, the target user is a student, and the local credit data includes one or more of the following:
library book borrowing records, canteen consumption records and campus violation records.
Optionally, the credit-related private data comprises one or more of:
consumption records, payment records, loan records and loan amounts.
In correspondence with the foregoing embodiments of the method for determining credit data, the present specification also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of:
sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users;
receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder;
carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
Optionally, the private data query request carries identification information of the determining party, and the encrypted private data is obtained by performing secure encryption on the private data of the user corresponding to the identification information and held by the corresponding data holding party.
Optionally, the secure encryption is obfuscated circuit encryption, and the secure decryption includes:
executing an inadvertent transmission algorithm, and acquiring private data of the target user after being encrypted by the garbled circuit from encrypted private data returned by the data holder;
and carrying out obfuscation circuit decryption on the private data of the target user after being encrypted by the obfuscation circuit to obtain the private data of the target user.
Optionally, the determining the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user includes:
and inputting the one or more pieces of private data of the target user obtained based on the security decryption and the local credit data of the target user into a preset function to obtain the comprehensive credit data of the target user.
Optionally, the target user is a student, and the local credit data includes one or more of the following:
library book borrowing records, canteen consumption records and campus violation records.
Optionally, the credit-related private data comprises one or more of:
consumption records, payment records, loan records and loan amounts.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements, etc. made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (13)
1. A credit data determination method is applied to a credit data determiner, and comprises the following steps:
sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users;
receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder;
carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
2. The method according to claim 1, wherein the private data query request carries identification information of the determining party, and the encrypted private data is obtained by a corresponding data holding party by securely encrypting the private data of the user corresponding to the identification information.
3. The method of claim 1, the secure encryption being a garbled circuit encryption, the secure decryption comprising:
executing an inadvertent transmission algorithm, and acquiring private data of the target user after being encrypted by the garbled circuit from encrypted private data returned by the data holder;
and carrying out obfuscation circuit decryption on the private data of the target user after being encrypted by the obfuscation circuit to obtain the private data of the target user.
4. The method of claim 3, wherein the determining the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user comprises:
and inputting the one or more pieces of private data of the target user obtained based on the security decryption and the local credit data of the target user into a preset function to obtain the comprehensive credit data of the target user.
5. The method of claim 1, the target user being a student, the local credit data comprising one or more of:
library book borrowing records, canteen consumption records and campus violation records.
6. The method of claim 1, the credit-related private data comprising one or more of:
consumption records, payment records, loan records and loan amounts.
7. A credit data determination apparatus applied to a credit data determination party, the apparatus comprising:
the system comprises a sending unit, a receiving unit and a sending unit, wherein the sending unit sends a private data query request to one or more data holders, and the data holders hold credit-related private data of a plurality of users;
the receiving unit is used for receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the private data held by the corresponding data holder;
the decryption unit is used for carrying out safe decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and the determining unit is used for determining the comprehensive credit data of the target user based on the one or more pieces of private data of the target user obtained by the secure decryption and the local credit data of the target user.
8. The apparatus according to claim 7, wherein the private data query request carries identification information of the determining party, and the encrypted private data is obtained by a corresponding data holder by securely encrypting the private data of a user corresponding to the identification information.
9. The apparatus of claim 7, the secure encryption being a garbled circuit encryption, the secure decryption comprising:
executing an inadvertent transmission algorithm, and acquiring private data of the target user after being encrypted by the garbled circuit from encrypted private data returned by the data holder;
and carrying out obfuscation circuit decryption on the private data of the target user after being encrypted by the obfuscation circuit to obtain the private data of the target user.
10. The apparatus of claim 9, the determination unit to:
and inputting the one or more pieces of private data of the target user obtained based on the security decryption and the local credit data of the target user into a preset function to obtain the comprehensive credit data of the target user.
11. The apparatus of claim 7, the target user being a student, the local credit data comprising one or more of:
library book borrowing records, canteen consumption records and campus violation records.
12. The apparatus of claim 7, the credit-related private data comprising one or more of:
consumption records, payment records, loan records and loan amounts.
13. An apparatus for determining credit data, comprising:
a processor;
a memory for storing machine executable instructions;
wherein, by reading and executing machine-executable instructions stored by the memory corresponding to the determination logic of credit data, the processor is caused to:
sending a private data query request to one or more data holders, wherein the data holders hold credit-related private data of a plurality of users;
receiving encrypted private data returned by the one or more data holders, wherein the encrypted private data is obtained by carrying out security encryption on the held private data by the corresponding data holder;
carrying out safety decryption processing on the encrypted private data returned by each data holder to obtain the private data of the target user;
and determining comprehensive credit data of the target user based on one or more pieces of private data of the target user obtained by secure decryption and the local credit data of the target user.
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| CN201911253517.0A CN111125753A (en) | 2019-12-09 | 2019-12-09 | Credit data determination method and device |
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| CN201911253517.0A CN111125753A (en) | 2019-12-09 | 2019-12-09 | Credit data determination method and device |
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