WO2020233038A1 - Blacklist cloud sharing verification method based on homomorphic encryption, and related apparatus - Google Patents

Abstract

The present application relates to cloud storage. Disclosed is a blacklist cloud sharing verification method based on homomorphic encryption. The method comprises: receiving a blacklist verification request sent by a first server and carrying a blacklist verification identifier and encrypted user information of a job seeker; searching a blacklist library for a first encrypted blacklist matching the blacklist verification identifier; acquiring a public key; performing, by means of the public key, homomorphic encryption on the encrypted user information and the first encrypted blacklist to obtain a homomorphic encryption result; sending, to a second server, a blacklist matching request carrying the homomorphic encryption result, wherein the blacklist matching request is used for indicating that the second server performs, by means of a private key, homomorphic decryption on the homomorphic encryption result to obtain a blacklist verification result; receiving a blacklist matching response sent by the second server and carrying the blacklist verification result; and sending, to the first server, a blacklist verification response carrying the blacklist verification result. By means of implementing the embodiments of the present application, the security and privacy of information are guaranteed during blacklist sharing.

Description

Homomorphic encryption-based blacklist cloud sharing verification method and related device

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on May 21, 2019, the application number is 2019104219862, and the application name is "The method and related device for homomorphic encryption-based blacklist cloud sharing verification", all of which The content is incorporated in this application by reference.

Technical field

This application relates to the field of computer technology, in particular to a method and related devices for blacklist cloud sharing verification based on homomorphic encryption.

Background technique

Currently, each enterprise maintains its own blacklist database to resist some malicious attacks. Although there may be some duplicate blacklists in the blacklist database between each company, because each company involves different fields, there are many different blacklists in the blacklist database between each company. With the development of the times, when companies are interviewing job applicants, they generally determine whether to recruit the job applicant based on the content of the job applicant’s resume and simple communication during the interview. However, this approach cannot take into account the conduct of the job applicant. Therefore, in order to achieve reasonable use of resources, many companies now place blacklists on third-party platforms, so that user information that needs to be verified can be matched with all blacklists in the third-party platform to determine the job search corresponding to the user information Whether the applicant has bad credit reporting, fraud, etc., so as to help the company whether to hire the job applicant.

However, in this sharing method, no matter it is the blacklist verification process or the process of uploading the blacklist to a third-party platform, since neither encryption is used, there is a problem of information being intercepted, which not only leads to the loss of user information, but also leads to blacklisting. List information leaked. In addition, since the third-party platform owns all the blacklist information uploaded by the company, all the blacklist information is exposed to the third-party platform, which is a bad experience for all enterprise users. Similarly, the user information of job applicants is also exposed to third-party platforms. Therefore, the security and privacy of information in this way are insufficient.

Summary of the invention

The embodiment of the application discloses a method and related device for verification of blacklist cloud sharing based on homomorphic encryption, implements the embodiment of the application, and implements the embodiment of the application to ensure the security and privacy of information under blacklist sharing.

The first aspect of the embodiments of the present application provides a blacklist cloud sharing verification method based on homomorphic encryption, including:

Receiving a blacklist verification request sent by the first server, where the blacklist verification request carries the blacklist verification identifier and the encrypted user information of the job applicant;

Searching for the first encrypted blacklist matching the blacklist verification identifier from the blacklist database;

Obtaining a public key stored in association with the first encryption blacklist;

Homomorphic encryption of the encrypted user information and the first encryption blacklist by using the public key to obtain a homomorphic encryption result;

Send a blacklist matching request to a second server, where the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key to encrypt the homomorphic result Perform homomorphic decryption to obtain the blacklist verification result;

Receiving a blacklist matching response sent by the second server, where the blacklist matching response carries the blacklist verification result;

Send a blacklist verification response to the first server, where the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to perform the blacklist verification result Risk assessment to obtain a risk assessment value to determine whether to hire the job applicant based on the risk assessment value.

The second aspect of the embodiments of the present application provides a blacklist cloud sharing verification device based on homomorphic encryption, including:

The first receiving module is configured to receive a blacklist verification request sent by the first server, wherein the blacklist verification request carries a blacklist verification identifier and encrypted user information of the job applicant;

A search module, which is used to search for the first encrypted blacklist matching the blacklist verification identifier from the blacklist library;

An obtaining module, configured to obtain a public key stored in association with the first encryption blacklist;

An encryption module, configured to perform homomorphic encryption on the encrypted user information and the first encryption blacklist by using the public key to obtain a homomorphic encryption result;

The first sending module is configured to send a blacklist matching request to a second server, wherein the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key Performing homomorphic decryption on the homomorphic encryption result to obtain a blacklist verification result;

A second receiving module, configured to receive a blacklist matching response sent by the second server, wherein the blacklist matching response carries the blacklist verification result;

The second sending module is configured to send a blacklist verification response to the first server, wherein the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to Perform risk assessment on the blacklist verification result to obtain a risk assessment value to determine whether to hire the job applicant based on the risk assessment value.

The third aspect of the embodiments of the present application provides an information processing electronic device, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory, and Instructions configured to be executed by the processor to execute steps in any one of an information processing method.

The fourth aspect of the embodiments of the present application provides a computer non-volatile readable storage medium, the computer non-volatile readable storage medium is used to store a computer program, and the stored computer program is executed by the processor, To implement the method described in any one of the information processing methods.

It can be seen that in the above technical solution, homomorphic decryption is used to obtain a blacklist verification result when the second server does not know user information, thereby realizing the separation of data processing rights and data ownership, and ensuring the security of all information Sex and privacy. At the same time, it has realized the rational use of blacklist resources, prevented companies from hiring job seekers with bad credit and fraud, and safeguarded corporate interests in all aspects. It also realizes the security and privacy of information under the blacklist sharing, and realizes the rational use of blacklist resources, prevents companies from hiring job applicants with bad credit and fraudulent behaviors, and safeguards corporate interests in all aspects.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

among them:

FIG. 1 is a schematic flowchart of a method for blacklist cloud sharing verification based on homomorphic encryption according to an embodiment of the application;

2 is a schematic flow diagram of another method for blacklist cloud sharing verification based on homomorphic encryption provided by an embodiment of the application;

FIG. 3 is a schematic diagram of a blacklist cloud sharing verification device based on homomorphic encryption provided by an embodiment of the application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of this application.

Detailed descriptions are given below.

The terms "first", "second", and "third" in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific sequence. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion.

First, referring to Fig. 1, Fig. 1 is a schematic flowchart of a method for verifying a blacklist cloud sharing based on homomorphic encryption according to an embodiment of the application. Wherein, as shown in FIG. 1, a method for blacklist cloud sharing verification based on homomorphic encryption provided by an embodiment of the present application may include:

101. The cloud verification center receives a blacklist verification request sent by the first server.

Wherein, the blacklist verification request carries the blacklist verification identifier and the encrypted user information of the job applicant.

The cloud verification center may include a server, for example.

102. The cloud verification center searches the blacklist database for the first encrypted blacklist that matches the blacklist verification identifier.

103. The cloud verification center obtains the public key stored in association with the first encryption blacklist.

104. The cloud verification center uses the public key to perform homomorphic encryption on the encrypted user information and the first encryption blacklist to obtain a homomorphic encryption result.

Optionally, the homomorphic encryption may be any one of addition homomorphism, multiplication homomorphism, mixed multiplication homomorphism, subtraction homomorphism, division homomorphism, algebraic homomorphism, and arithmetic homomorphism, for example.

Among them, homomorphic encryption is a cryptographic technique based on the computational complexity theory of mathematical problems. The homomorphic encrypted data is processed to obtain an output, and the output is decrypted. The result is the same as the output period information obtained by processing the unencrypted original data in the same method.

105. The cloud verification center sends a blacklist matching request to the second server.

Wherein, the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key to homomorphically decrypt the homomorphic encryption result to obtain a blacklist verification result.

106. The cloud verification center receives a blacklist matching response sent by the second server.

Wherein, the blacklist matching response carries the blacklist verification result.

107. The cloud verification center sends a blacklist verification response to the first server.

Wherein, the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to perform a risk assessment on the blacklist verification result to obtain a risk assessment value based on the The risk assessment value determines whether to hire the job applicant.

Refer to FIG. 2, which is a schematic flowchart of another method for blacklist cloud sharing verification based on homomorphic encryption provided by an embodiment of the application. Wherein, as shown in FIG. 2, a method for blacklist cloud sharing verification based on homomorphic encryption provided by an embodiment of the present application may include:

201. The cloud verification center receives a public key request sent by the first server.

Wherein, the public key request carries a public key identifier, and the public key identifier is generated by the first server based on the blacklist verification identifier.

202. The cloud verification center searches for the public key matching the public key identifier from the blacklist database.

203. The cloud verification center sends a public key response to the first server.

Wherein, the public key response carries the public key, and the public key response is used to instruct the first server to use the public key to encrypt user information to be encrypted to obtain the encrypted user information.

Optionally, the user information to be encrypted may include, for example, name, gender, age, ID number, contact information, graduate school, etc.

204. The cloud verification center receives the blacklist verification request sent by the first server.

Wherein, the blacklist verification request carries the blacklist verification identifier and the encrypted user information of the job applicant.

The cloud verification center may include a server, for example.

205. The cloud verification center searches the blacklist database for the first encrypted blacklist that matches the blacklist verification identifier.

Optionally, in the first aspect, in a possible implementation manner of the present application, before the searching from the blacklist database for the first encrypted blacklist matching the blacklist verification identifier, the method further includes: Receive a request to join a cloud verification center sent by the second server, where the request to join a cloud verification center carries the identity authentication information and identity authentication public key of the second server; and determine the Internet Protocol address in the identity authentication information Comply with the preset legal Internet protocol address; use the identity authentication public key to perform identity authentication on the signature information in the identity authentication information; when the identity authentication is passed, send a blacklist request to the second server, where the The blacklist request is used to instruct the second server to use the public key to encrypt the first blacklist to be encrypted to obtain the first encrypted blacklist; receive the blacklist response sent by the second server, where: The blacklist response carries the first encryption blacklist and the public key; the public key and the first encryption blacklist are associated and stored in the blacklist library.

Among them, IP address refers to Internet Protocol Address (Internet Protocol Address, also translated as Internet Protocol Address), which is the abbreviation of IP Address. The IP address is a unified address format provided by the IP protocol. It assigns a logical address to each network and each host on the Internet to shield differences in physical addresses.

Optionally, the signature information is obtained by the second server using the identity authentication private key to encrypt the enterprise information.

Among them, the enterprise information may include, for example, enterprise name, organization code, contact information, business address, business scope, etc.

It can be seen that in the above technical solution, the cloud verification center receives the request to join the cloud verification center that carries the identity authentication information and the identity verification public key of the second server sent by the second server. Provide convenience for verification; determine that the Internet Protocol address in the identity authentication information conforms to the preset legal Internet protocol address to ensure the legitimacy of the logical address of the second server; use the identity authentication public key to authenticate the signature information in the identity authentication information to ensure The signature information carried by the second server has not been tampered with, ensuring the legitimacy of the second server; when the identity authentication is passed, a blacklist request is sent to the second server, where the blacklist request is used to instruct the second server to adopt public The key encrypts the first blacklist to be encrypted to obtain the first encrypted blacklist. Only when the identity authentication is passed, it is agreed that the second server can send the encrypted blacklist to the cloud verification center, thus ensuring a reasonable joining principle; The blacklist response sent by the second server, where the blacklist response carries the first encrypted blacklist and the public key to obtain the public key, which can allow the first server to encrypt user information to be encrypted, or use the public key to implement homomorphic encryption; The public key and the first encrypted blacklist are stored in the blacklist database in association with each other, so that the cloud verification center can obtain the public key. In summary, by setting the conditions for joining the cloud verification center, the accuracy of the blacklist is ensured and pave the way for the subsequent construction of a benign blacklist database.

Optionally, based on the first aspect, in the first possible implementation manner of this application, the blacklist response further carries an encrypted blacklist identifier and J pieces of blacklist term data in the first blacklist to be encrypted , J is a positive integer, the encrypted blacklist identifier is used to indicate that the J pieces of blacklist deadline data belong to the first encrypted blacklist, and each of the J pieces of blacklist deadline data is used for Indicates the time limit for the personal bad information to be recorded in the first blacklist to be encrypted. After the associated storage of the public key and the first encrypted blacklist in the blacklist library, the method further includes: Obtain the time when the public key and the first encrypted blacklist are stored in the blacklist library in association with each other at a preset time interval to obtain N storage periods, where N is a positive integer; and the N storage periods are Input the preset encryption blacklist storage period function in the order of time to obtain N output period data; in the order of time, the N output period data are sequentially connected to each of the J pieces of blacklist period data. The deadline data is compared, and it is determined that there is first output deadline data larger than H pieces of blacklist deadline data in the N pieces of output deadline data, where the H pieces of blacklist deadline data belong to the J pieces of blacklist deadline data, 0 <H≤J and H is an integer; call the blacklist overdue identifier generation algorithm for the H pieces of blacklist expiration data to generate H blacklist overdue identifiers, wherein each of the H blacklist overdue identifiers is overdue The identifier is used to indicate that the personal bad information has expired; sending a blacklist update request to the second server, wherein the blacklist update request carries the H blacklist expiration identifiers, and the blacklist update request is used for Instruct the second server to delete H pieces of personal bad information matching the H blacklist expiration identifiers in the first blacklist to be encrypted, to obtain a second blacklist to be encrypted, and use the public key to pair the The second blacklist to be encrypted is encrypted to obtain a second encrypted blacklist; the blacklist update response sent by the second server is received, wherein the blacklist update response carries the second encrypted blacklist; it will communicate with the public The first encryption blacklist stored in association with the key is replaced with the second encryption blacklist.

Wherein, J can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, N may be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, H can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Among them, in an optional scheme, the blacklist deadline data can be as shown in the following table:

Blacklist period (days)	2
Blacklist period (days)	15
Blacklist period (days)	30
…	…

The left ellipsis in the above table indicates the blacklist period (days), and the right ellipsis indicates the specific number of days.

Optionally, the preset time may include, for example, half an hour, one day, three days, one week, two weeks, one month, three months, six months, one year and other times.

Among them, the preset time can be set by the administrator in advance. Or the preset time can also be recorded in the configuration file, and the preset time can be determined by querying the configuration file.

Optionally, the preset encryption blacklist storage period function is y=x+sin(x/6), where y is the output period data, and x is the storage period.

Among them, personal bad information may include, for example, name, gender, age, ID number, contact information, reason for dishonesty, time of dishonesty, incident of dishonesty, location of dishonesty, etc.

It can be seen that in the above technical solution, the public key and the time when the first encrypted blacklist is associated and stored in the blacklist library are obtained every preset time interval to obtain N storage time periods, and the storage time period is obtained through each preset time interval, A dynamic monitoring blacklist library will be implemented; N storage periods are input into the preset encryption blacklist storage period function in the order of time, and N output period data are obtained, and the N storage periods are input into the preset encryption in the order of time The blacklist storage period function realizes the orderly acquisition of output period data, which speeds up the processing speed of the cloud verification center; the N output period data are sequentially processed with each blacklist period data in the J blacklist period data in chronological order By comparison, it is determined that there are first output deadline data larger than H pieces of blacklist deadline data in the N output deadline data, and by sequentially comparing the N output deadline data with each blacklist deadline data in the J blacklist deadline data, quickly Obtain the first output deadline data that is greater than H blacklist deadline data among the N output deadline data, so as to determine that H blacklist deadline data in the J blacklist deadline data has expired; call black for H blacklist deadline data The list overdue identifier generation algorithm generates H blacklist overdue identifiers, of which, each of the H blacklist overdue identifiers is used to indicate that personal bad information has expired, and H blacklist overdue identifiers are generated, which are the second server Prepare for deleting invalid personal bad information in the blacklist to be encrypted; send a blacklist update request to the second server, where the blacklist update request carries H blacklist expiration identifiers, and the blacklist update request is used to instruct the second server to H pieces of personal bad information matching the H blacklist expiration identifiers in the first blacklist to be encrypted are deleted, and the second blacklist to be encrypted is obtained, and the second blacklist to be encrypted is encrypted with the public key to obtain the second encrypted blacklist , So that the second server deletes H pieces of personal bad information according to the H blacklist expiration flags to obtain the second blacklist to be encrypted, and then uses the public key to encrypt the second blacklist to be encrypted to obtain the second encrypted blacklist, Prepare for the subsequent sending of the second encrypted blacklist to the cloud verification center; receive the blacklist update response sent by the second server, where the blacklist update response carries the second encrypted blacklist to realize the transmission of data; it will be associated with the public key The stored first encrypted blacklist is replaced with the second encrypted blacklist, thereby realizing the deletion of invalid personal bad information in the blacklist database, saving storage space and reducing the storage cost of the cloud verification center.

206. The cloud verification center obtains the public key stored in association with the first encryption blacklist.

207. The cloud verification center uses the public key to perform homomorphic encryption on the encrypted user information and the first encryption blacklist to obtain a homomorphic encryption result.

Optionally, the homomorphic encryption may be any one of addition homomorphism, multiplication homomorphism, mixed multiplication homomorphism, subtraction homomorphism, division homomorphism, algebraic homomorphism, and arithmetic homomorphism, for example.

Among them, homomorphic encryption is a cryptographic technique based on the computational complexity theory of mathematical problems. The homomorphic encrypted data is processed to obtain an output, and the output is decrypted. The result is the same as the output period information obtained by processing the unencrypted original data in the same method.

208. The cloud verification center sends a blacklist matching request to the second server.

Wherein, the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key to homomorphically decrypt the homomorphic encryption result to obtain a blacklist verification result.

209. The cloud verification center receives a blacklist matching response sent by the second server.

Wherein, the blacklist matching response carries the blacklist verification result.

210. The cloud verification center sends a blacklist verification response to the first server.

Wherein, the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to perform a risk assessment on the blacklist verification result to obtain a risk assessment value based on the The risk assessment value determines whether to hire the job applicant.

Optionally, in the first aspect, in a possible implementation manner of the present application, the method further includes: receiving the blacklist verification request sent by the first server, wherein the blacklist verification request carries M blacklist verification identifiers and M encrypted user information of M job applicants; search for M encrypted blacklists matching the M blacklist verification identifiers from the blacklist database, where the M blacklists The list verification identifiers correspond to the M encrypted blacklists one-to-one; obtain the M public keys stored in association with the M encrypted blacklists; use the M public keys to pair the M encrypted user information and the Perform homomorphic encryption on M encryption blacklists to obtain M homomorphic encryption results, where the i-th homomorphic encryption result in the M homomorphic encryption results is determined by the i-th public key in the M public keys The key encrypts the i-th encrypted user information and the i-th encrypted blacklist, the i-th encrypted user information belongs to the M encrypted user information, and the i-th encrypted blacklist belongs to the M Encrypted blacklist, 0<i≤M and i is an integer; sending M blacklist matching requests to M second servers, where the M second servers correspond to the M blacklist matching requests one-to-one, The M blacklist matching requests carry the M homomorphic encryption results, and the i-th blacklist matching request in the M blacklist matching requests is used to instruct the i-th second server to use the i-th private key Performing homomorphic decryption on the i-th homomorphic encryption result to obtain the i-th group of blacklist verification results in the M groups of blacklist verification results, the i-th second server belongs to the M second servers, the The i-th group of blacklist verification results contains K blacklist verification results, and K is a positive integer; M blacklist matching responses sent by the M second servers are received, where the M second servers are There is a one-to-one correspondence between M blacklist matching responses, and the M blacklist matching responses carry the M groups of blacklist verification results; each group of blacklist verification results in the M groups of blacklist verification results are verified according to a preset non-repetition rule The results are screened to obtain N sets of blacklist verification results, where each set of blacklist verification results in the N sets of blacklist verification results includes L blacklist verification results, N is a positive integer, N=M, L≤ K and L are positive integers; call the file generation interface to generate a blacklist verification report containing the N groups of blacklist verification results; send the blacklist verification response to the first server, where the blacklist verification response carries The blacklist verification report, and the blacklist verification response is used to instruct the first server to extract the N sets of blacklist verification results in the blacklist verification report, and risk the N sets of blacklist verification results After evaluation, N risk assessment values are obtained, so as to determine whether to hire the M job applicants based on the N risk assessment values.

Wherein, M can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, i can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, K can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, L can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Wherein, N may be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Optionally, based on the first aspect, in the first possible implementation manner of this application, before the calling file generation interface generates a blacklist verification report containing the N groups of blacklist verification results, the method further include:

S1: Set n to an integer whose initial value is 1;

S2: Check whether n is less than or equal to N, if yes, execute S3, if not, execute S9;

S3: Obtain the L blacklist verification results in the nth group of blacklist verification results, where the nth group of blacklist verification results belong to the N groups of blacklist verification results;

S4: Extract L pieces of blacklist term data from the L pieces of blacklist verification results;

S5: Determine L risk levels corresponding to the L pieces of blacklist term data, where the blacklist term data is proportional to the risk level;

S6: Arrange the L pieces of blacklist term data corresponding to the L risk levels in the order of risk level from high to low, and obtain the L blacklist verification results after the arrangement;

S7: Add the arranged L blacklist verification results to the nth group of blacklist verification results;

S8: Assign (n+1) to n and return to execute S2;

S9: End the arrangement.

Wherein, n can be equal to 1, 2, 3, 5, 6, 11, 13, 20 or other values, for example.

Optionally, based on the first aspect or the first possible implementation manner of the first aspect, in the second possible implementation manner of the present application, the determination of L pieces of blacklist term data corresponding to L Risk level, including:

Filter out the blacklist term data with the largest blacklist term from the L pieces of blacklist term data;

Comparing the blacklist deadline data with preset blacklist deadline data to determine whether the blacklist deadline data is greater than the preset blacklist deadline data;

If the blacklist deadline data is greater than the preset blacklist deadline data, determining a risk level evaluation function corresponding to the blacklist deadline data from a risk level evaluation function library;

Input the L pieces of blacklist term data into the risk level evaluation function to obtain L pieces of risk level evaluation data;

Extracting the risk grade assessment data with the largest risk grade assessment data from the L pieces of risk grade assessment data;

Determine the preset risk level evaluation weight corresponding to the risk level evaluation data;

The L pieces of risk level evaluation data are calculated according to the preset risk level evaluation weights to obtain L risk levels.

Among them, in an optional scheme, different risk level evaluation functions corresponding to different blacklist deadline data can be as shown in the following table:

Maximum blacklist period (days)	Default blacklist period data (days)	Risk rating function
15	10	y=x/a+cos(x-a)
30	10	y=x a/1 +tan(x/a)
…	…	…

The x in the above table represents the blacklist period with the largest blacklist period, a represents the preset blacklist period data, and y represents the risk level evaluation data.

Among them, in an optional scheme, different risk level evaluation data corresponding to different preset risk level evaluation weights can be as shown in the following table:

Risk assessment data	Preset risk level assessment weight
1.5	1.5/3+0.28
3.2	3.2/3+0.28
…	…

Optionally, based on the first aspect or the first or second possible implementation manner of the first aspect, in a third possible implementation manner of the present application, the method further includes:

If the blacklist term data is not greater than the preset blacklist term data, input the L pieces of blacklist term data into a risk prediction model to obtain a risk prediction value;

Comparing the risk prediction value with a preset risk prediction value to determine whether the risk prediction value exceeds the preset risk prediction value;

If the risk prediction value exceeds the preset risk prediction value, determining the first set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction value;

Send a warning message to the first server, where the warning message carries the risk prediction value and the first set of blacklist verification results, and the warning message is used to instruct the first server to predict based on the risk The value marks the job seeker corresponding to the first set of blacklist verification results as untrusted job seekers.

Optionally, based on the first aspect or the first or second or third possible implementation manner of the first aspect, in the fourth possible implementation manner of this application, the public key request also carries For the member information of the first server, the method further includes:

If the risk prediction value does not exceed the preset risk prediction value, determining the member level in the member information;

Comparing the member level with the preset member level to determine that the member level is higher than the preset member level;

Input the risk prediction value into a risk prediction scoring model to obtain a risk prediction score;

Determining the second set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction score;

A risk prediction score message carrying the risk prediction score and the second set of blacklist verification results is sent to the first server, wherein the risk prediction score message is used to instruct the first server to predict the risk based on the risk The job applicants corresponding to the second group of blacklist verification results are evaluated by scoring, and it is determined whether to admit the job applicants corresponding to the second group of blacklist verification results.

Referring to FIG. 3, a blacklist cloud sharing verification device 300 based on homomorphic encryption provided by an embodiment of the present application may include:

The first receiving module 301 is configured to receive a blacklist verification request sent by the first server.

Wherein, the blacklist verification request carries the blacklist verification identifier and the encrypted user information of the job applicant.

The cloud verification center may include a server, for example.

Optionally, the first receiving module 301 is further configured to receive a public key request sent by the first server, where the public key request carries a public key identifier, and the public key identifier is determined by the first server based on the The blacklist verification identifier is generated; the search module 302 is also used to search for the public key matching the public key identifier from the blacklist library; the first receiving module 301 is also used to send The first server sends a public key response, where the public key response carries the public key, and the public key response is used to instruct the first server to use the public key to encrypt user information to be encrypted to obtain the encryption User Info.

Optionally, the device further includes a processing module 308, and the first receiving module 301 is further configured to receive a request to join a cloud verification center sent by the second server, wherein the request to join a cloud verification center carries the The identity authentication information and identity authentication public key of the second server; the processing module 308 is used to determine that the Internet protocol address in the identity authentication information meets the preset legal Internet protocol address; the processing module 308 is also used to use The identity authentication public key performs identity authentication on the signature information in the identity authentication information; the first sending module 305 is further configured to send a blacklist request to the second server when the identity authentication is passed, where: The blacklist request is used to instruct the second server to use the public key to encrypt the first blacklist to be encrypted to obtain the first encrypted blacklist; the first receiving module 301 is also used to receive The blacklist response sent by the second server, where the blacklist response carries the first encrypted blacklist and the public key; the processing module 308 is further configured to combine the public key and the first The encrypted blacklist is associated and stored in the blacklist library.

Optionally, the blacklist response further carries an encrypted blacklist identifier and J pieces of blacklist expiration data in the first blacklist to be encrypted, where J is a positive integer, and the encrypted blacklist identifier is used to indicate that J Pieces of blacklist expiration data belong to the first encrypted blacklist, and each piece of blacklist expiration data in the J pieces of blacklist expiration data is used to indicate the time period during which personal bad information is recorded on the first blacklist to be encrypted, The processing module 308 is further configured to obtain the time when the public key and the first encrypted blacklist are stored in the blacklist library in association with each other for a preset period of time, to obtain N storage periods, where N is a positive integer The processing module 308 is also used to input the N storage periods in the order of time into the preset encryption blacklist storage period function to obtain N output period data; the processing module 308 is also used to The N pieces of output deadline data are compared with each piece of blacklist deadline data in the J pieces of blacklist deadline data in chronological order, and it is determined that there are more than H pieces of blacklist deadline data among the N pieces of output deadline data. The first output deadline data, wherein, the H pieces of blacklist deadline data belong to the J pieces of blacklist deadline data, 0<H≤J and H is an integer; the processing module 308 is also used to compare the H pieces The blacklist expiration date data calls the blacklist overdue indicator generation algorithm to generate H blacklist overdue indicators, where each of the H blacklist overdue indicators is used to indicate that the personal bad information has expired; first The sending module 305 is further configured to send a blacklist update request to the second server, where the blacklist update request carries the H blacklist expiration identifiers, and the blacklist update request is used to indicate the second The server deletes H pieces of personal bad information matching the H blacklist expiration identifiers from the first blacklist to be encrypted to obtain a second blacklist to be encrypted, and uses the public key to blacklist the second to be encrypted The list is encrypted to obtain a second encrypted blacklist; the first receiving module 301 is further configured to receive a blacklist update response sent by the second server, wherein the blacklist update response carries the second encrypted blacklist The processing module 308 is also used to replace the first encrypted blacklist stored in association with the public key with the second encrypted blacklist.

Optionally, the first receiving module is further configured to receive the blacklist verification request sent by the first server, wherein the blacklist verification request carries M blacklist verification identifiers and M job applicants’ information M encrypted user information; the search module 302 is also used to search for M encrypted blacklists matching the M blacklist verification identifiers from the blacklist library, wherein the M blacklist verification identifiers One-to-one correspondence with the M encrypted blacklists; the obtaining module 303 is also used to obtain M public keys stored in association with the M encrypted blacklists; the encryption module 304 is also used to use the M public keys perform homomorphic encryption on the M encrypted user information and the M encrypted blacklists to obtain M homomorphic encryption results, where the i-th homomorphic of the M homomorphic encryption results The encryption result is obtained by encrypting the i-th encrypted user information and the i-th encrypted blacklist by the i-th public key among the M public keys, and the i-th encrypted user information belongs to the M encrypted users Information, the i-th encrypted blacklist belongs to the M encrypted blacklists, 0<i≤M and i is an integer; the first sending module 305 is also used to send M blacklists to M second servers A list matching request, wherein the M second servers correspond to the M blacklist matching requests one-to-one, the M blacklist matching requests carry the M homomorphic encryption results, and the M blacklists The i-th blacklist matching request in the matching request is used to instruct the i-th second server to use the i-th private key to homomorphically decrypt the i-th homomorphic encryption result to obtain the first among the M groups of blacklist verification results. The i group of blacklist verification results, the i-th second server belongs to the M second servers, the i-th group of blacklist verification results include K blacklist verification results, and K is a positive integer; A receiving module 301 is further configured to receive M blacklist matching responses sent by the M second servers, where the M second servers correspond to the M blacklist matching responses one-to-one, and the M A blacklist matching response carries the M groups of blacklist verification results; the processing module 308 is further configured to screen each group of blacklist verification results in the M groups of blacklist verification results according to a preset non-repetition rule, In order to obtain N sets of blacklist verification results, each of the N sets of blacklist verification results includes L blacklist verification results, N is a positive integer, N=M, L≤K and L is A positive integer; the processing module 308 is also used to call the file generation interface to generate a blacklist verification report containing the N groups of blacklist verification results; the first sending module 305 is also used to send to the first server The blacklist verification response, wherein the blacklist verification response carries the blacklist verification report, and the blacklist verification response is used to instruct the first server to extract the N groups in the blacklist verification report Blacklist verification results, risk assessment is performed on the N groups of blacklist verification results, and N risk assessment values are obtained, so as to determine whether or not based on the N risk assessment values Employ the M job applicants.

Optionally, the processing module 308 is also used for

S1: Set n to an integer whose initial value is 1;

S2: Check whether n is less than or equal to N, if yes, execute S3, if not, execute S9;

S3: Obtain the L blacklist verification results in the nth group of blacklist verification results, where the nth group of blacklist verification results belong to the N groups of blacklist verification results;

S4: Extract L pieces of blacklist term data from the L pieces of blacklist verification results;

S5: Determine L risk levels corresponding to the L pieces of blacklist term data, where the blacklist term data is proportional to the risk level;

S6: Arrange the L pieces of blacklist term data corresponding to the L risk levels in the order of risk levels from high to low, and obtain the L blacklist verification results after the arrangement;

S7: Add the arranged L blacklist verification results to the nth group of blacklist verification results;

S8: Assign (n+1) to n and return to execute S2;

S9: End the arrangement.

Optionally, the processing module 308 is further configured to filter out the blacklist deadline data with the largest blacklist deadline from the L pieces of blacklist deadline data; and compare the blacklist deadline data with the preset blacklist deadline data Comparison to determine whether the blacklist expiration data is greater than the preset blacklist expiration data; if the blacklist expiration data is greater than the preset blacklist expiration data, it is determined from the risk level evaluation function library to The risk level evaluation function corresponding to the blacklist term data; the L pieces of blacklist term data are respectively input into the risk level evaluation function to obtain L pieces of risk level evaluation data; the risk is extracted from the L pieces of risk level evaluation data The risk grade assessment data with the largest grade assessment data; determine the preset risk grade assessment weight corresponding to the risk grade assessment data; calculate the L pieces of risk grade assessment data according to the preset risk grade assessment weight to obtain L risk grades.

Optionally, the processing module 308 is further configured to, if the blacklist period data is not greater than the preset blacklist period data, input the L pieces of blacklist period data into the risk prediction model to obtain a risk prediction The processing module 308 is also used to compare the risk prediction value with a preset risk prediction value to determine whether the risk prediction value exceeds the preset risk prediction value; the processing module 308 also If the risk prediction value exceeds the preset risk prediction value, determine the first set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction value; the first sending The module 305 is further configured to send a warning message to the first server, where the warning message carries the risk prediction value and the first set of blacklist verification results, and the warning message is used to indicate the first set of blacklist verification results. The server marks the job seeker corresponding to the first set of blacklist verification results as untrusted job seekers based on the risk prediction value.

Optionally, the public key request also carries member information of the first server, and the processing module 308 is further configured to determine the member if the risk prediction value does not exceed the preset risk prediction value The member level in the information; the processing module 308 is also used to compare the member level with a preset member level to determine that the member level is higher than the preset member level; the processing module 308 is also used to The risk prediction value is input into a risk prediction scoring model to obtain a risk prediction score; the processing module 308 is also used to determine the second set of blacklists in the N sets of blacklist verification results corresponding to the risk prediction score Verification result; the first sending module 305 is further configured to send a risk prediction score message carrying the risk prediction score and the second set of blacklist verification results to the first server, wherein the risk prediction score The message is used to instruct the first server to evaluate the job seeker corresponding to the second set of blacklist verification results based on the risk prediction score, and determine whether to admit the job seeker corresponding to the second set of blacklist verification results .

The searching module 302 is configured to search for the first encrypted blacklist matching the blacklist verification identifier from the blacklist database.

The obtaining module 303 is configured to obtain the public key stored in association with the first encryption blacklist.

The encryption module 304 is configured to use the public key to perform homomorphic encryption on the encrypted user information and the first encryption blacklist to obtain a homomorphic encryption result.

Optionally, the homomorphic encryption may be any one of addition homomorphism, multiplication homomorphism, mixed multiplication homomorphism, subtraction homomorphism, division homomorphism, algebraic homomorphism, and arithmetic homomorphism, for example.

Among them, homomorphic encryption is a cryptographic technique based on the computational complexity theory of mathematical problems. The homomorphic encrypted data is processed to obtain an output, and the output is decrypted. The result is the same as the output period information obtained by processing the unencrypted original data in the same method.

The first sending module 305 is configured to send a blacklist matching request to the second server.

Wherein, the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key to homomorphically decrypt the homomorphic encryption result to obtain a blacklist verification result.

The second receiving module 306 is configured to receive a blacklist matching response sent by the second server.

Wherein, the blacklist matching response carries the blacklist verification result.

The second sending module 307 is configured to send a blacklist verification response to the first server.

Wherein, the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to perform a risk assessment on the blacklist verification result to obtain a risk assessment value based on the The risk assessment value determines whether to hire the job applicant.

The embodiment of the present application also provides an electronic device for information processing, including a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured The instructions are executed by the processor to execute the steps in any one of the information processing methods.

The embodiment of the present application also provides a computer non-volatile readable storage medium, the computer non-volatile readable storage medium is used to store a computer program, and the stored computer program is executed by the processor to realize A method according to any one of the information processing methods.

In the several embodiments provided in this application, it should be understood that the disclosed device may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other divisions in actual implementation, for example, multiple modules or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or modules, and may be in electrical or other forms.

The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed to multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules.

If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present application essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage The medium includes several instructions to enable a computer device (which may be a personal computer, a merchant node, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program code .

As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present application, not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, a person of ordinary skill in the art should understand that: The technical solutions recorded in the embodiments are modified, or some of the technical features are equivalently replaced; these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims (20)

1. The blacklist cloud sharing verification method based on homomorphic encryption is characterized by including:

   Receiving a blacklist verification request sent by the first server, where the blacklist verification request carries the blacklist verification identifier and the encrypted user information of the job applicant;

   Searching for the first encrypted blacklist matching the blacklist verification identifier from the blacklist database;

   Obtaining a public key stored in association with the first encryption blacklist;

   Homomorphic encryption of the encrypted user information and the first encryption blacklist by using the public key to obtain a homomorphic encryption result;

   Send a blacklist matching request to a second server, where the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key to encrypt the homomorphic result Perform homomorphic decryption to obtain the blacklist verification result;

   Receiving a blacklist matching response sent by the second server, where the blacklist matching response carries the blacklist verification result;

   Send a blacklist verification response to the first server, where the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to perform the blacklist verification result Risk assessment to obtain a risk assessment value to determine whether to hire the job applicant based on the risk assessment value.
2. The method according to claim 1, wherein before said receiving the blacklist verification request sent by the first server, the method further comprises:

   Receiving a public key request sent by the first server, where the public key request carries a public key identifier, and the public key identifier is generated by the first server based on the blacklist verification identifier;

   Searching for the public key matching the public key identifier from the blacklist library;

   Send a public key response to the first server, where the public key response carries the public key, and the public key response is used to instruct the first server to use the public key to encrypt user information to be encrypted to obtain The encrypted user information.
3. The method according to claim 1, characterized in that before said searching from a blacklist library for a first encrypted blacklist matching the blacklist verification identifier, the method further comprises:

   Receiving a request to join a cloud verification center sent by the second server, where the request to join a cloud verification center carries identity authentication information and an identity authentication public key of the second server;

   Determining that the internet protocol address in the identity authentication information conforms to a preset legal internet protocol address;

   Using the identity authentication public key to perform identity authentication on the signature information in the identity authentication information;

   When the identity authentication is passed, a blacklist request is sent to the second server, where the blacklist request is used to instruct the second server to use the public key to encrypt the first blacklist to be encrypted to obtain the The first encryption blacklist;

   Receiving a blacklist response sent by the second server, where the blacklist response carries the first encryption blacklist and the public key;

   The public key and the first encryption blacklist are associated and stored in the blacklist database.
4. The method according to claim 3, wherein the blacklist response further carries an encrypted blacklist identifier and J pieces of blacklist term data in the first blacklist to be encrypted, J is a positive integer, and the encrypted blacklist The blacklist identifier is used to indicate that the J pieces of blacklist expiration data belong to the first encrypted blacklist, and each piece of blacklist expiration data in the J pieces of blacklist expiration data is used to indicate that personal bad information is recorded in the first encrypted blacklist. A time limit for the blacklist to be encrypted, after the associated storage of the public key and the first encrypted blacklist in the blacklist library, the method further includes:

   Acquiring the time when the public key and the first encrypted blacklist are stored in the blacklist library in association with each other at a preset time interval to obtain N storage time intervals, where N is a positive integer;

   Input the N storage periods into a preset encryption blacklist storage period function in a time sequence to obtain N output period data;

   Compare the N output deadline data with each blacklist deadline data in the J blacklist deadline data in chronological order, and determine that there are more than H blacklist deadlines in the N output deadline data The first output deadline data of the data, wherein the H pieces of blacklist deadline data belong to the J pieces of blacklist deadline data, 0<H≤J and H is an integer;

   The blacklist overdue identifier generation algorithm is invoked on the H pieces of blacklist expiration data to generate H blacklist overdue identifiers, wherein each of the H blacklist overdue identifiers is used to represent the personal bad information expired;

   Send a blacklist update request to the second server, where the blacklist update request carries the H blacklist expiration identifiers, and the blacklist update request is used to instruct the second server to set the first waiting The H pieces of personal bad information that match the H blacklist expiration identifiers in the encryption blacklist are deleted to obtain a second blacklist to be encrypted, and the public key is used to encrypt the second blacklist to be encrypted to obtain a second Encryption blacklist;

   Receiving a blacklist update response sent by the second server, where the blacklist update response carries the second encrypted blacklist;

   Replacing the first encryption blacklist stored in association with the public key with the second encryption blacklist.
5. The method according to any one of claims 1 to 4, wherein the method further comprises:

   Receiving the blacklist verification request sent by the first server, wherein the blacklist verification request carries M blacklist verification identifiers and M encrypted user information of M job applicants;

   Search for M encrypted blacklists matching the M blacklist verification identifiers from the blacklist database, where the M blacklist verification identifiers correspond to the M encrypted blacklists one-to-one;

   Acquiring M public keys stored in association with the M encryption blacklists;

   Use the M public keys to homomorphically encrypt the M encrypted user information and the M encrypted blacklist to obtain M homomorphic encryption results, where the i-th of the M homomorphic encryption results A homomorphic encryption result is obtained by encrypting the i-th encrypted user information and the i-th encrypted blacklist by the i-th public key among the M public keys, and the i-th encrypted user information belongs to the M Encrypted user information, the i-th encrypted blacklist belongs to the M encrypted blacklists, 0<i≤M and i is an integer;

   Send M blacklist matching requests to M second servers, where the M second servers correspond to the M blacklist matching requests one-to-one, and the M blacklist matching requests carry the M identical The i-th blacklist matching request in the M blacklist matching requests is used to instruct the i-th second server to use the i-th private key to homomorphically decrypt the i-th homomorphic encryption result Obtain the i-th group of blacklist verification results in the M groups of blacklist verification results, the i-th second server belongs to the M second servers, and the i-th group of blacklist verification results include K blacklist verifications As a result, K is a positive integer;

   M blacklist matching responses sent by the M second servers are received, where the M second servers correspond to the M blacklist matching responses one-to-one, and the M blacklist matching responses carry the M group blacklist verification result;

   Each group of blacklist verification results in the M groups of blacklist verification results is screened according to a preset non-repetition rule to obtain N groups of blacklist verification results, wherein each group of blacklist verification results in the N groups of blacklist verification results The list verification result includes L blacklist verification results, where N is a positive integer, N=M, L≤K and L is a positive integer;

   Calling the file generation interface to generate a blacklist verification report containing the N groups of blacklist verification results;

   Send the blacklist verification response to the first server, where the blacklist verification response carries the blacklist verification report, and the blacklist verification response is used to instruct the first server to extract the blacklist verification According to the verification results of the N groups of blacklists in the report, a risk assessment is performed on the verification results of the N groups of blacklists to obtain N risk assessment values, so as to determine whether to hire the M job applicants based on the N risk assessment values .
6. The method according to claim 5, characterized in that, before the calling file generation interface generates a blacklist verification report containing the N groups of blacklist verification results, the method further comprises:

   S1: Set n to an integer whose initial value is 1;

   S2: Check whether n is less than or equal to N, if yes, execute S3, if not, execute S9;

   S3: Obtain the L blacklist verification results in the nth group of blacklist verification results, where the nth group of blacklist verification results belong to the N group of blacklist verification results;

   S4: Extract L pieces of blacklist term data from the L pieces of blacklist verification results;

   S5: Determine L risk levels corresponding to the L pieces of blacklist term data, where the blacklist term data is proportional to the risk level;

   S6: Arrange the L pieces of blacklist term data corresponding to the L risk levels in the order of risk levels from high to low, and obtain the L blacklist verification results after the arrangement;

   S7: Add the arranged L blacklist verification results to the nth group of blacklist verification results;

   S8: Assign (n+1) to n and return to execute S2;

   S9: End the arrangement.
7. The method according to claim 6, wherein the determining the L risk levels corresponding to the L pieces of blacklist term data includes:

   Filter out the blacklist term data with the largest blacklist term from the L pieces of blacklist term data;

   Comparing the blacklist deadline data with preset blacklist deadline data to determine whether the blacklist deadline data is greater than the preset blacklist deadline data;

   If the blacklist deadline data is greater than the preset blacklist deadline data, determining a risk level evaluation function corresponding to the blacklist deadline data from a risk level evaluation function library;

   Input the L pieces of blacklist term data into the risk level evaluation function to obtain L pieces of risk level evaluation data;

   Extracting the risk grade assessment data with the largest risk grade assessment data from the L pieces of risk grade assessment data;

   Determine the preset risk level evaluation weight corresponding to the risk level evaluation data;

   The L pieces of risk level evaluation data are calculated according to the preset risk level evaluation weights to obtain L risk levels.
8. The method according to claim 7, wherein the method further comprises: if the blacklist deadline data is not greater than the preset blacklist deadline data, inputting the L pieces of blacklist deadline data into the risk prediction Model to get the risk prediction value;

   Comparing the risk prediction value with a preset risk prediction value to determine whether the risk prediction value exceeds the preset risk prediction value;

   If the risk prediction value exceeds the preset risk prediction value, determining the first set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction value;

   Send a warning message to the first server, where the warning message carries the risk prediction value and the first set of blacklist verification results, and the warning message is used to instruct the first server to predict based on the risk The value marks the job seeker corresponding to the first set of blacklist verification results as untrusted job seekers.
9. The method according to any one of claims 1 to 7, wherein the public key request also carries member information of the first server, and the method further comprises:

   If the risk prediction value does not exceed the preset risk prediction value, determining the member level in the member information;

   Comparing the member level with the preset member level to determine that the member level is higher than the preset member level;

   Input the risk prediction value into a risk prediction scoring model to obtain a risk prediction score;

   Determining the second set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction score;

   A risk prediction score message carrying the risk prediction score and the second set of blacklist verification results is sent to the first server, wherein the risk prediction score message is used to instruct the first server to predict the risk based on the risk The job applicants corresponding to the second group of blacklist verification results are evaluated by scoring, and it is determined whether to admit the job applicants corresponding to the second group of blacklist verification results.
10. A blacklist cloud sharing verification device based on homomorphic encryption is characterized by comprising:

    The first receiving module is configured to receive a blacklist verification request sent by the first server, wherein the blacklist verification request carries a blacklist verification identifier and encrypted user information of the job applicant;

    A search module, which is used to search for the first encrypted blacklist matching the blacklist verification identifier from the blacklist library;

    An obtaining module, configured to obtain a public key stored in association with the first encryption blacklist;

    An encryption module, configured to perform homomorphic encryption on the encrypted user information and the first encryption blacklist by using the public key to obtain a homomorphic encryption result;

    The first sending module is configured to send a blacklist matching request to a second server, wherein the blacklist matching request carries the homomorphic encryption result, and the blacklist matching request is used to instruct the second server to use a private key Performing homomorphic decryption on the homomorphic encryption result to obtain a blacklist verification result;

    A second receiving module, configured to receive a blacklist matching response sent by the second server, wherein the blacklist matching response carries the blacklist verification result;

    The second sending module is configured to send a blacklist verification response to the first server, wherein the blacklist verification response carries the blacklist verification result, and the blacklist verification response is used to instruct the first server to Perform risk assessment on the blacklist verification result to obtain a risk assessment value to determine whether to hire the job applicant based on the risk assessment value.
11. The device according to claim 10, wherein the first receiving module is further configured to receive a public key request sent by the first server, wherein the public key request carries a public key identifier, and the public key identifier Generated by the first server based on the blacklist verification identifier; the search module is further configured to search for the public key matching the public key identifier from the blacklist library; the first receiving module, It is also used to send a public key response to the first server, where the public key response carries the public key, and the public key response is used to instruct the first server to use the public key to perform encrypted user information. Encryption to obtain the encrypted user information.
12. The device according to claim 10, wherein the device further comprises a processing module, and the first receiving module is further configured to receive a request to join a cloud verification center sent by the second server, wherein the joining The cloud verification center requests to carry the identity authentication information and identity authentication public key of the second server; the processing module is configured to determine that the Internet Protocol address in the identity authentication information conforms to a preset legal Internet Protocol address; the processing module , Is also configured to use the identity authentication public key to perform identity authentication on the signature information in the identity authentication information; the first sending module is also used to send a blacklist to the second server when the identity authentication is passed Request, wherein the blacklist request is used to instruct the second server to use the public key to encrypt the first blacklist to be encrypted to obtain the first encrypted blacklist; the first receiving module also uses After receiving the blacklist response sent by the second server, wherein the blacklist response carries the first encrypted blacklist and the public key; the processing module is further configured to combine the public key with the public key The first encryption blacklist is associated and stored in the blacklist library.
13. The device according to claim 12, wherein the blacklist response further carries an encrypted blacklist identifier and J pieces of blacklist term data in the first blacklist to be encrypted, J is a positive integer, and the encrypted blacklist The blacklist identifier is used to indicate that the J pieces of blacklist expiration data belong to the first encrypted blacklist, and each piece of blacklist expiration data in the J pieces of blacklist expiration data is used to indicate that personal bad information is recorded in the first encrypted blacklist. A time limit for the blacklist to be encrypted, the processing module is further configured to obtain the time when the public key and the first encrypted blacklist are associated and stored in the blacklist library at intervals of a preset period of time, to obtain N storage Time period, where N is a positive integer; the processing module is further configured to input the N storage time periods into a preset encrypted blacklist storage period function in time order to obtain N output period data; the processing module , And also used to compare the N pieces of output deadline data with each piece of blacklist deadline data in the J pieces of blacklist deadline data in chronological order, and determine that there is more than H The first output deadline data of pieces of blacklist deadline data, wherein the H pieces of blacklist deadline data belong to the J pieces of blacklist deadline data, 0<H≤J and H is an integer; the processing module is also used for The blacklist overdue identifier generation algorithm is invoked on the H pieces of blacklist expiration data to generate H blacklist overdue identifiers, wherein each of the H blacklist overdue identifiers is used to represent the personal bad information Has expired; the first sending module is also used to send a blacklist update request to the second server, wherein the blacklist update request carries the H blacklist expiration identifiers, and the blacklist update request is used to indicate The second server deletes H pieces of personal bad information matching the H blacklist expiration identifiers in the first blacklist to be encrypted to obtain a second blacklist to be encrypted, and uses the public key to pair the first The second encrypted blacklist is encrypted to obtain a second encrypted blacklist; the first receiving module is further configured to receive a blacklist update response sent by the second server, where the blacklist update response carries the second Encryption blacklist; the processing module is further configured to replace the first encryption blacklist stored in association with the public key with the second encryption blacklist.
14. The device according to any one of claims 10 to 13, wherein the first receiving module is further configured to receive the blacklist verification request sent by the first server, wherein the blacklist verification request Request to carry M blacklist verification identifiers and M encrypted user information of M job applicants;

    The search module is further configured to search for M encrypted blacklists matching the M blacklist verification identifiers from the blacklist library, wherein the M blacklist verification identifiers are the same as the M encrypted blacklists. One-to-one correspondence between lists;

    The obtaining module is further configured to obtain M public keys stored in association with the M encrypted blacklists;

    The encryption module is further configured to use the M public keys to perform homomorphic encryption on the M encrypted user information and the M encrypted blacklists to obtain M homomorphic encryption results, wherein the M The i-th homomorphic encryption result in the homomorphic encryption result is obtained by encrypting the i-th encrypted user information and the i-th encrypted blacklist by the i-th public key among the M public keys. Pieces of encrypted user information belong to the M pieces of encrypted user information, the i-th encrypted blacklist belongs to the M pieces of encrypted blacklist, 0<i≤M and i is an integer;

    The first sending module is further configured to send M blacklist matching requests to M second servers, where the M second servers correspond to the M blacklist matching requests one-to-one, and the M The blacklist matching request carries the M homomorphic encryption results, and the i-th blacklist matching request in the M blacklist matching requests is used to instruct the i-th second server to use the i-th private key to pair the i homomorphic encryption results are homomorphically decrypted to obtain the i-th group of blacklist verification results in the M groups of blacklist verification results, the i-th second server belongs to the M second servers, and the i-th group of blacklist verification results The list verification result contains K blacklist verification results, and K is a positive integer;

    The first receiving module is further configured to receive M blacklist matching responses sent by the M second servers, where the M second servers correspond to the M blacklist matching responses one-to-one, so The M blacklist matching responses carry the M groups of blacklist verification results;

    The processing module is further configured to screen each group of blacklist verification results in the M groups of blacklist verification results according to a preset non-repetition rule to obtain N groups of blacklist verification results, wherein the N groups of blacklist verification results Each group of blacklist verification results in the list verification results includes L blacklist verification results, where N is a positive integer, N=M, L≤K and L is a positive integer;

    The processing module is further configured to call a file generation interface to generate a blacklist verification report containing the N groups of blacklist verification results;

    The first sending module is further configured to send the blacklist verification response to the first server, wherein the blacklist verification response carries the blacklist verification report, and the blacklist verification response is used to instruct all The first server extracts the N sets of blacklist verification results in the blacklist verification report, performs risk assessment on the N sets of blacklist verification results, and obtains N risk assessment values based on the N risk assessments The value determines whether to hire the M job applicants.
15. The device according to claim 14, wherein the processing module is also used for

    S1: Set n to an integer whose initial value is 1;

    S2: Check whether n is less than or equal to N, if yes, execute S3, if not, execute S9;

    S3: Obtain the L blacklist verification results in the nth group of blacklist verification results, where the nth group of blacklist verification results belong to the N groups of blacklist verification results;

    S4: Extract L pieces of blacklist term data from the L pieces of blacklist verification results;

    S5: Determine L risk levels corresponding to the L pieces of blacklist term data, where the blacklist term data is proportional to the risk level;

    S6: Arrange the L pieces of blacklist term data corresponding to the L risk levels in the order of risk levels from high to low, and obtain the L blacklist verification results after the arrangement;

    S7: Add the arranged L blacklist verification results to the nth group of blacklist verification results;

    S8: Assign (n+1) to n and return to execute S2;

    S9: End the arrangement.
16. The device according to claim 15, wherein the processing module is further configured to filter out the blacklist deadline data with the largest blacklist deadline from the L pieces of blacklist deadline data; and convert the blacklist deadline data It is compared with the preset blacklist term data to determine whether the blacklist term data is greater than the preset blacklist term data; if the blacklist term data is greater than the preset blacklist term data, the risk level Determine the risk level evaluation function corresponding to the blacklist term data in the evaluation function library; input the L pieces of blacklist term data into the risk level evaluation function to obtain L pieces of risk level evaluation data; The risk grade assessment data with the largest risk grade assessment data is extracted from the pieces of risk grade assessment data; the preset risk grade assessment weight corresponding to the risk grade assessment data is determined; the L pieces of risk grade assessment data are performed according to the preset risk grade assessment weight Calculate to get L risk levels.
17. The device according to claim 16, wherein the processing module is further configured to input the L pieces of blacklist deadline data if the blacklist deadline data is not greater than the preset blacklist deadline data A risk prediction model to obtain a risk prediction value; the processing module is also used to compare the risk prediction value with a preset risk prediction value to determine whether the risk prediction value exceeds the preset risk prediction value; The processing module is further configured to determine the first set of blacklist verification results among the N sets of blacklist verification results corresponding to the risk prediction value if the risk prediction value exceeds the preset risk prediction value The first sending module is further configured to send a warning message to the first server, wherein the warning message carries the risk prediction value and the first set of blacklist verification results, and the warning message is used for Instruct the first server to mark job seekers corresponding to the first group of blacklist verification results as untrusted job seekers based on the risk prediction value.
18. The device according to any one of claims 10 to 17, wherein the public key request also carries member information of the first server, and the processing module is further configured to: if the risk prediction value does not exceed The preset risk prediction value determines the member level in the member information; the processing module is also used to compare the member level with the preset member level to determine that the member level is higher than the preset member level Membership level; the processing module is also used to input the risk prediction value into a risk prediction scoring model to obtain a risk prediction score; the processing module is also used to determine the N groups of blacks corresponding to the risk prediction score The second set of blacklist verification results in the list verification results; the first sending module is further configured to send to the first server a risk prediction score carrying the risk prediction score and the second set of blacklist verification results Message, wherein the risk prediction score message is used to instruct the first server to evaluate job applicants corresponding to the second set of blacklist verification results based on the risk prediction score, and determine whether to admit the second set of blacklist verification results. Job applicants corresponding to the group blacklist verification result.
19. An electronic device for information processing, which is characterized by comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured by the The processor executes the instructions to execute the steps in the method of any one of claims 1-9.
20. A computer non-volatile readable storage medium, wherein the computer non-volatile readable storage medium is used to store a computer program, and the stored computer program is executed by the processor to implement claim 1 -9 The method described in any one.

Images