Identity recognition method, system and related device in multi-service scene

Abstract

The invention discloses a method, a system and a related device for identity recognition under multiple service scenes, which are used for integrating identity recognition functions under different service scenes, reducing the management difficulty and improving the service efficiency. The method comprises the following steps: acquiring an identity recognition request sent by a service party, wherein the identity recognition request comprises an identity recognition type and encrypted identity information; determining an algorithm type specified by the service party, and decrypting the encrypted identity information according to the algorithm type to obtain identity information of the target user; analyzing the identity information according to the identity recognition type to obtain a first analysis result; obtaining a second analysis result in a database according to the identity recognition type and the first analysis result; comparing whether the first analysis result and the second analysis result are consistent or not; if yes, the identity recognition result information of the target user is assembled according to the second analysis result; and encrypting the identity recognition result information according to the algorithm type, and returning the encrypted identity recognition result information to the service party.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method, system and related devices for identity recognition in multiple business scenarios. Background Art

[0002] Identity recognition technology is an indispensable part of the modern security system. It uses a variety of methods and means to confirm the identity information of individuals or entities to ensure their authenticity and legitimacy. Identity recognition technology has been widely used in many fields such as security, finance, and the Internet. In the process of identity recognition, multiple factors are usually involved, including but not limited to personal information, biometrics, and personal credentials. Due to the sensitivity of these identity information, strict encryption and decryption must be performed during use to prevent data leakage or unauthorized access.

[0003] In the prior art, by encrypting sensitive data, the security of data during storage and transmission can be ensured. At the same time, the decryption process ensures that authorized users or systems can access the data when needed to complete identity authentication or other related operations. In order to achieve this goal, the identity recognition system usually adopts advanced encryption algorithms and security protocols, such as AES, RSA, etc., and adopts multi-factor authentication mechanisms to enhance security. However, since different business scenarios use different identity recognition systems, the data is obviously decentralized, difficult to manage and integrate uniformly, and easily forms information islands, which increases the difficulty of data management and maintenance. And due to the lack of unified standards and specifications, there are differences in the operating procedures, authority settings, etc. of various identity recognition systems, which greatly reduces business efficiency. Summary of the invention

[0004] The present application provides a method, system and related devices for identity identification in multiple business scenarios, which are used to integrate identity identification functions in different business scenarios, reduce management difficulty and improve business efficiency.

[0005] The first aspect of the present application provides a method for identity identification in a multi-service scenario, including:

[0006] Obtaining an identity identification request sent by a business party, wherein the identity identification request includes an identity identification type and encrypted identity information;

[0007] Determine the algorithm type specified by the business party, and decrypt the encrypted identity information according to the algorithm type to obtain the identity information of the target user;

[0008] Parsing the identity information according to the identity recognition type to obtain a first parsing result;

[0009] Acquire a second parsing result in a database according to the identity recognition type and the first parsing result, wherein identity information of a plurality of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user;

[0010] comparing whether the first analysis result and the second analysis result are consistent;

[0011] If yes, assembling the identity recognition result information of the target user according to the second analysis result;

[0012] The identity recognition result information is encrypted according to the algorithm type, and the encrypted identity recognition result information is returned to the business party.

[0013] Optionally, after comparing whether the first analysis result and the second analysis result are consistent, the method further includes:

[0014] If not, assembling the target user's identity recognition failure information according to the failure reason;

[0015] The identity recognition failure information is encrypted according to the algorithm type, and the encrypted identity recognition failure information is returned to the business party.

[0016] Optionally, acquiring a second parsing result from a database according to the identity recognition type and the first parsing result includes:

[0017] querying in a database whether there is identity information related to the first parsing result according to the identity recognition type;

[0018] If so, determining the hard parsing result of the identity information related to the first parsing result in the database as the second parsing result;

[0019] If not, a second parsing result is obtained from the cooperation channel party according to the identity recognition type and the first parsing result.

[0020] Optionally, assembling the target user's identity recognition result information according to the second parsing result includes:

[0021] Determining the identification record of the target user according to the second analysis result;

[0022] Assemble the identity recognition result information of the target user according to the second parsing result and the recognition record.

[0023] Optionally, before determining the algorithm type specified by the business party and decrypting the encrypted identity information according to the algorithm type, the method further includes:

[0024] Perform an integrity check on the identity identification request.

[0025] Optionally, determining the algorithm type specified by the business party includes:

[0026] The algorithm type specified by the business party is determined according to the identifier carried in the identity identification request.

[0027] Optionally, determining the algorithm type specified by the business party includes:

[0028] The algorithm type specified by the business party is determined according to the business type associated with the identity identification request.

[0029] The second aspect of the present application provides a system for identity recognition in multiple business scenarios, including:

[0030] An acquiring unit, configured to acquire an identity identification request sent by a business party, wherein the identity identification request includes an identity identification type and encrypted identity information;

[0031] A decryption unit, used to determine the algorithm type specified by the service provider, and decrypt the encrypted identity information according to the algorithm type to obtain the identity information of the target user;

[0032] A first parsing unit, configured to parse the identity information according to the identity recognition type to obtain a first parsing result;

[0033] A second parsing unit, configured to obtain a second parsing result from a database according to the identity recognition type and the first parsing result, wherein identity information of a plurality of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user;

[0034] A comparing unit, used for comparing whether the first analysis result and the second analysis result are consistent;

[0035] a first assembling unit, configured to assemble the target user's identity recognition result information according to the second analytic result when the comparing unit determines that the first analytic result and the second analytic result are consistent;

[0036] The first encryption unit is used to encrypt the identity recognition result information according to the algorithm type and return the encrypted identity recognition result information to the business party.

[0037] Optionally, the system further includes:

[0038] a second assembling unit, configured to assemble the target user's identity recognition failure information according to a failure reason when the comparing unit determines that the first parsing result and the second parsing result are inconsistent;

[0039] The second encryption unit is used to encrypt the identity recognition failure information according to the algorithm type and return the encrypted identity recognition failure information to the business party.

[0040] Optionally, the second parsing unit is specifically used for:

[0041] querying in a database whether there is identity information related to the first parsing result according to the identity recognition type;

[0042] If so, determining the hard parsing result of the identity information related to the first parsing result in the database as the second parsing result;

[0043] If not, a second parsing result is obtained from the cooperation channel party according to the identity recognition type and the first parsing result.

[0044] Optionally, the first assembly unit is specifically used for:

[0045] Determining the identification record of the target user according to the second analysis result;

[0046] Assemble the identity recognition result information of the target user according to the second parsing result and the recognition record.

[0047] Optionally, the system further includes:

[0048] A verification unit is used to perform integrity verification on the identity identification request.

[0049] Optionally, the decryption unit is specifically used for:

[0050] The algorithm type specified by the business party is determined according to the identifier carried in the identity identification request.

[0051] Optionally, the decryption unit is further used for:

[0052] The algorithm type specified by the business party is determined according to the business type associated with the identity identification request.

[0053] A third aspect of the present application provides a device for identity recognition in a multi-service scenario, the device comprising:

[0054] Processor, memory, input-output unit, and bus;

[0055] The processor is connected to the memory, the input and output unit, and the bus;

[0056] The memory stores a program, and the processor calls the program to execute the first aspect and any optional method for identity identification in multiple business scenarios in the first aspect.

[0057] In a fourth aspect, the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the method for identity identification in the first aspect and any optional multi-business scenario in the first aspect is performed.

[0058] It can be seen from the above technical solutions that this application has the following advantages:

[0059] First, the identity identification request sent by the business party is obtained, and the algorithm type specified by the business party is determined. The encrypted identity information is decrypted through the algorithm type to achieve unified management of various algorithm types, which significantly reduces the complexity and cost of docking between different identity identification systems. Secondly, by introducing a unified identity information parsing and verification mechanism, that is, firstly, the decrypted identity information is parsed according to the identity identification type specified by the business party to generate a first parsing result. Then, according to the identity identification type and the first parsing result, a database with a large amount of user identity information pre-stored is accessed to obtain the second parsing result and perform consistency verification. This ensures that each business scenario can operate under a unified parsing and verification standard, effectively eliminating the differences in operating procedures and authority settings caused by inconsistent standards, which not only simplifies the identity identification process, but also ensures the consistency of identity identification in different business scenarios and data reliability.

[0060] Through the standardized process of decryption, parsing and result assembly, different business scenarios no longer need to develop or maintain their own identity recognition systems separately, thereby improving the compatibility of the system and overall business efficiency. In addition, the identity recognition method of this application provides higher flexibility and scalability for system expansion and third-party access, allowing the business system to respond to complex identity recognition needs more efficiently and securely. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0062] Figure 1 A flowchart of an embodiment of a method for identity identification in a multi-service scenario provided by the present application;

[0063] Figure 2 A flowchart of another embodiment of the method for identity identification in multi-service scenarios provided by the present application;

[0064] Figure 3A schematic diagram of an embodiment of a flow chart for obtaining a second parsing result in a method for identity recognition in a multi-business scenario provided by the present application;

[0065] Figure 4 A schematic diagram of an embodiment of assembling identity recognition result information in a method for identity recognition in multiple business scenarios provided by the present application;

[0066] Figure 5 A schematic diagram of the structure of an embodiment of a system for identity recognition in multiple business scenarios provided by this application;

[0067] Figure 6 A schematic diagram of the structure of an embodiment of a device for identity recognition in multiple business scenarios provided in this application. DETAILED DESCRIPTION

[0068] The present application provides a method, system and related devices for identity identification in multiple business scenarios, which are used to integrate identity identification functions in different business scenarios, reduce management difficulty and improve business efficiency.

[0069] It should be noted that the method for identity recognition in multiple business scenarios provided by this application can be applied to terminals, systems and servers. For example, the terminal can be a smart phone or computer, tablet computer, smart TV, smart watch, portable computer terminal or a fixed terminal such as a desktop computer. For the convenience of explanation, this application uses an identity recognition system, hereinafter referred to as the system, as an example for the execution subject.

[0070] See also Figure 1 , Figure 1 An embodiment of a method for identity identification in a multi-service scenario provided by the present application includes:

[0071] S101, obtaining an identity identification request sent by a business party, where the identity identification request includes an identity identification type and encrypted identity information;

[0072] In different business scenarios, the business party usually needs to authenticate the user before providing the corresponding service to ensure the legitimacy of the user's identity and business security. The business party specifically refers to the application system or service that initiates the identity identification request. For example, the business party can be a merchant, bank, e-commerce platform, government agency, etc. Due to the different requirements of different business scenarios, the format and content of the identity identification request may be different. Therefore, the system should have a unified interface for receiving identity identification requests from different business parties. This interface is compatible with multiple request formats to ensure that the system can flexibly respond to various business needs.

[0073] Specifically, the system receives identity identification requests from different business parties through a unified interface. The identity identification request contains encrypted user identity information, such as user ID, user identity information (such as name, ID number, mobile phone number, address) and biometric data (such as fingerprint, facial recognition data), etc. In addition, the identity identification request also contains a field for the identity identification type, which is used to indicate the type of identity information and identification method used for identity identification. Common types of identity identification include: biometric identification (such as fingerprint, facial recognition), personal three-factor identification (name, ID number and mobile phone number / bank card number), enterprise four-factor identification (enterprise name, unified social credit code, legal representative name and legal representative identity certificate), etc., which are not limited here.

[0074] S102, determining the algorithm type specified by the business party, and decrypting the encrypted identity information according to the algorithm type to obtain the identity information of the target user;

[0075] In order to ensure that the user's identity information is not stolen or tampered with during transmission, the business party usually encrypts the identity information. This encryption operation is implemented through a specific encryption algorithm, and different business parties may use different encryption algorithms to encrypt data. Therefore, after the system receives the identity recognition request, it must first determine the type of encryption algorithm used by the business party, and then select the corresponding decryption algorithm based on the algorithm type to decrypt the encrypted identity information in order to obtain the target user's real identity information.

[0076] Encryption algorithms are mainly divided into two categories:

[0077] Symmetric encryption algorithm: uses the same key for encryption and decryption. Common symmetric encryption algorithms include AES (Advanced Encryption Standard) and DES (Data Encryption Standard).

[0078] Asymmetric encryption algorithm: uses a pair of keys (public key and private key) for encryption and decryption. Common asymmetric encryption algorithms include RSA, ECC (elliptic curve encryption), etc.

[0079] In some scenarios, hybrid encryption technology may also be used. Since each type of encryption algorithm can be further subdivided according to its own rules, it leads to compatibility issues when decrypting across systems or platforms. Therefore, the system needs to support multiple algorithms according to the connected business parties to ensure compatibility in different business scenarios.

[0080] S103, parsing the identity information according to the identity recognition type to obtain a first parsing result;

[0081] The system needs to parse the decrypted identity information according to the identity recognition type. The parsing specifically refers to processing and converting the various data fields in the identity information according to specific formats and rules to facilitate subsequent verification and comparison. Parsing of identity information usually includes steps such as data field extraction, verification (such as check digit verification, format verification) and data cleaning (such as removing invalid characters or spaces).

[0082] By parsing the identity information, the system will obtain the first parsing result, which contains the core elements of identity recognition and serves as the basic data for subsequent identity recognition and comparison. For example, if the identity recognition type is personal three-factor recognition, the system will parse the decrypted identity information to obtain the first parsing result: name, ID number, mobile phone number and other fields; if it is corporate four-factor recognition, the system will parse the decrypted identity information to obtain the first parsing result: corporate name, unified social credit code and other fields.

[0083] S104, obtaining a second parsing result in a database according to the identity recognition type and the first parsing result, wherein identity information of a number of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user;

[0084] In order to ensure the legitimacy and authenticity of the user's identity, the system needs to compare the parsed identity information with the user information pre-stored in the database. The database pre-stores the hard-parsed identity information of several users, which is collected and stored when the user registers, opens an account or verifies, and has a high degree of accuracy and completeness. By comparing with the hard-parsed user's identity information, the system can effectively confirm the authenticity of the current identity recognition request.

[0085] In order to perform an effective comparison, the system needs to query the corresponding identity information, that is, the second analysis result, from the database based on the identity recognition type and the first analysis result. Specifically, the system determines the conditions for querying in the database based on the identity recognition type and the first analysis result. The query conditions are different for different identity recognition types. For example, if the identity recognition type is personal three-factor recognition, the first analysis result contains the target user's ID number, name, and mobile phone number / bank card number information. Since the ID number is generally regarded as a unique and stable identifier, the system will use the ID number as the main query condition at this time to perform a matching query in the database. After the system queries the corresponding ID number, it will horizontally search for other information associated with the ID number (such as name and mobile phone number / bank card number), and use this information together as the second analysis result.

[0086] S105, comparing the first analysis result and the second analysis result to see whether they are consistent;

[0087] By comparing the first analysis result and the second analysis result, that is, comparing the identity information submitted by the business party and the identity information stored in the database, the system can determine whether the user's identity is legal and authentic. If the two are consistent, it means that the target user's identity recognition is passed, and step 106 is executed.

[0088] S106, assembling the target user's identity recognition result information according to the second analysis result;

[0089] If the system determines that the first analysis result and the second analysis result are consistent, the identity recognition result information is assembled according to the second analysis result, including assembling the user's identity information, verification status, verification timestamp and other data into a complete response information to facilitate the business party to perform subsequent processing, such as authorized access, transaction confirmation, etc.

[0090] S107. Encrypt the identity recognition result information according to the algorithm type, and return the encrypted identity recognition result information to the business party.

[0091] In order to enhance the security of the entire system and prevent potential data leakage or attacks, the system must encrypt the identity recognition result information before returning it. First, the algorithm type of the encryption algorithm needs to be determined, and the algorithm type should be consistent with the algorithm type determined in step S102 to ensure the compatibility of encryption and decryption. The system encrypts the assembled identity recognition result information according to the algorithm type, and returns the encrypted identity recognition result information to the business party, completing the entire identity recognition process.

[0092] In this embodiment, the identity identification request sent by the business party is first obtained, and the algorithm type specified by the business party is determined. The encrypted identity information is decrypted by the algorithm type to achieve unified management of various algorithm types, which significantly reduces the complexity and cost of docking between different identity identification systems. Secondly, by introducing a unified identity information parsing and verification mechanism, that is, firstly, the decrypted identity information is parsed according to the identity identification type specified by the business party to generate a first parsing result. Then, according to the identity identification type and the first parsing result, a database with a large amount of user identity information pre-stored is accessed to obtain the second parsing result and perform consistency verification. This ensures that each business scenario can operate under a unified parsing and verification standard, effectively eliminating the differences in operating procedures and authority settings caused by inconsistent standards, which not only simplifies the identity identification process, but also ensures the consistency of identity identification in different business scenarios and data reliability.

[0093] Through the standardized process of decryption, parsing and result assembly, different business scenarios no longer need to develop or maintain their own identity recognition systems separately, thereby improving the compatibility of the system and overall business efficiency. In addition, the identity recognition method of this application provides higher flexibility and scalability for system expansion and third-party access, allowing the business system to respond to complex identity recognition needs more efficiently and securely.

[0094] The following is a detailed description of the identity recognition method in multiple business scenarios provided by this application. Figure 2 , Figure 2 Another embodiment of the method for identity identification in a multi-service scenario provided by the present application includes:

[0095] S201. Obtain an identity identification request sent by a business party, where the identity identification request includes an identity identification type and encrypted identity information;

[0096] In this embodiment, step S201 is similar to step S101 in the above embodiment and will not be described again here.

[0097] S202, performing integrity check on the identity identification request;

[0098] In this embodiment, after the system receives the identity identification request sent by the business party, it first needs to perform an integrity check on the identity identification request. The integrity check step is usually performed before decryption and parsing to ensure the validity and security of the request. Specifically, the integrity check can be performed through technologies such as HMAC, digital signatures, or hash values, which are not limited here. The system uses the generated or extracted integrity check value according to the integrity check method agreed with the business party to compare with the actual received identity identification request content. If the two match, it means that the identity identification request data has not been tampered with during the transmission process, and the integrity check passes. If the check fails, the system will refuse to process the identity identification request and generate an error response to return to the business party, indicating that there is a data integrity problem.

[0099] S203, determining the algorithm type specified by the business party, and decrypting the encrypted identity information according to the algorithm type to obtain the identity information of the target user;

[0100] In the identity verification process, different business parties may use different encryption algorithms to protect the user's identity information. These encryption algorithms are usually selected based on business needs, risk levels, regulatory requirements and other factors. Therefore, when processing identity verification requests, the system first needs to determine the encryption algorithm type specified by the business party. Specifically, the system can determine the algorithm type specified by the business party in the following two ways:

[0101] 1. Determine the algorithm type specified by the business party based on the identifier carried in the identity identification request;

[0102] When sending an identification request, the business party may carry a specific identifier in the identification request, which may be the business party identity identifier or the algorithm identifier. If the identification request carries the algorithm identifier, the system can directly determine the algorithm type specified by the business party based on the algorithm identifier. If the identification request only carries the business party identity identifier, the system will query the algorithm type previously set by the business party from the business party's personal profile or account database based on the business party identity identifier. These configurations may include security-related settings such as the encryption algorithm and key management preferences specified by the business party when it first accesses the system.

[0103] 2. Determine the algorithm type specified by the business party based on the business type associated with the identity identification request;

[0104] Each identification request is usually associated with a specific business type, such as financial transactions, user logins, corporate authentication, etc., and different business types may correspond to different security requirements and encryption algorithms. The system can determine the specific business type associated with the identification request by the identity of the business party, and then select the corresponding decryption algorithm based on the business type. For example, financial services involving high security requirements may use stronger asymmetric encryption algorithms (such as RSA), while ordinary user logins may use symmetric encryption algorithms (such as AES).

[0105] S204, parsing the identity information according to the identity recognition type to obtain a first parsing result;

[0106] S205, obtaining a second parsing result in a database according to the identity recognition type and the first parsing result, wherein identity information of a number of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user;

[0107] In this embodiment, steps S204-S205 are similar to steps S103-S104 of the aforementioned embodiment and are not described again here.

[0108] S206, comparing the first analysis result and the second analysis result to see whether they are consistent;

[0109] In this embodiment, if the system determines that the first analysis result and the second analysis result are consistent, step 207 is executed. If the system determines that the first analysis result and the second analysis result are inconsistent, step 209 is executed.

[0110] S207, assembling the target user's identity recognition result information according to the second analysis result;

[0111] S208. Encrypt the identity recognition result information according to the algorithm type, and return the encrypted identity recognition result information to the business party;

[0112] In this embodiment, steps S207-S208 are similar to steps S106-S107 of the aforementioned embodiment and are not described again here.

[0113] S209, assembling target user's identity recognition failure information according to the failure reason;

[0114] In this embodiment, if the system determines that the first parsing result and the second parsing result are inconsistent, it means that the identity recognition has failed. At this time, the system records the reason for the failure and then assembles the identity recognition failure information of the target user according to the reason for the failure. Common reasons for failure include but are not limited to: inconsistent user identity information, encryption / decryption errors, database query failure, etc. Each failure reason corresponds to a different error code and error message. The identity recognition failure information can include error code, error message description, failure time, etc. to help the business party understand the reason for the failure and take appropriate measures.

[0115] S210: Encrypt the identity recognition failure information according to the algorithm type, and return the encrypted identity recognition failure information to the business party.

[0116] Unencrypted failure information may be intercepted or tampered with during transmission. Therefore, the system also needs to encrypt the identity recognition failure information according to the algorithm type specified by the business party, and then return the encrypted identity recognition failure information to the business party, making the entire identity recognition process more secure and reliable. Finally, the business party can obtain the identity recognition failure information through decryption and reject the target user's business request.

[0117] In the above step S104 or S205, the system can not only obtain the second analysis result in the internal database, but also obtain the second analysis result through external cooperation channels to ensure the accuracy and comprehensiveness of identity recognition. Figure 3 , Figure 3 To obtain an embodiment of the second parsing result, the method includes:

[0118] S301, querying in a database whether there is identity information related to the first parsing result according to the identity recognition type;

[0119] The system determines the query conditions and scope according to the identity recognition type, and queries the database to see whether there is identity information related to the first parsing result. For example, if the identity recognition type is personal three-factor recognition, the system will perform an exact match query in the database based on the ID card number in the first parsing result to find out whether there is corresponding identity information. If there is, step S302 is executed; if not, step S303 is executed.

[0120] S302, determining a hard parsing result of identity information related to the first parsing result in the database as a second parsing result;

[0121] If the system finds identity information related to the first analysis result in the database, this information is regarded as legal identity data confirmed within the system. At this time, the system needs to determine the hard analysis results of the identity information related to the first analysis result as the second analysis result for subsequent identity comparison and verification.

[0122] S303: Obtain a second parsing result from the cooperation channel party according to the identity recognition type and the first parsing result.

[0123] In some cases, the system's internal database may not store the target user's required identity information under the current identity recognition type. At this time, it is necessary to obtain the latest or supplementary identity information from external cooperative channel parties (such as credit reporting agencies, third-party certification agencies, etc.). That is, when the system finds that there is no identity information related to the first resolution result in the database, it will conduct additional queries through the cooperative channel party to obtain an accurate second resolution result. Specifically, the system will generate a query request and send it to the cooperative channel party based on the identity recognition type and the first resolution result. For example, if it is a four-factor identification of an enterprise, the system may query the industrial and commercial department or a third-party certification agency for the company's registration information. The identity information returned by the cooperative channel party will be received by the system and stored in the database as the second resolution result.

[0124] In this embodiment, the system can not only effectively realize identity recognition based on the internal database, but also obtain more identity information through cooperative channels to ensure the accuracy and comprehensiveness of identity recognition. It ensures that even if the system's internal database data is insufficient, identity recognition can still be completed through external resources, thereby improving the reliability and security of the system.

[0125] In the above step S106 or S207, the system can combine the identification record and permission information of the target user to assemble the target user's identity recognition result information. Figure 4 , Figure 4 In one embodiment of assembling the target user's identity recognition result information, the method includes:

[0126] S401, determining the identification record of the target user according to the second analysis result;

[0127] Based on the identity information in the second parsing result, the system queries the identification record of the target user, which is used to record the historical situation of the user's identity identification at different times and in different business scenarios, including but not limited to the following information: business party type, identification timestamp, type of identity identification used, identification result (success or failure), reason for identification failure, identification frequency, etc. By analyzing these identification records, the system or business party can evaluate the behavior pattern of the target user, thereby discovering potential risks and providing more comprehensive identity identification suggestions for the business party.

[0128] S402: Assemble the target user's identity recognition result information according to the second parsing result and the recognition record.

[0129] Based on the second analysis result, that is, the identity information and identification record of the target user in the database, the system assembles complete identity identification result information to help the business party understand the behavior of the target user in different business scenarios and assist in determining whether the target user has potential risks, thereby providing richer and more secure identity identification services.

[0130] The following is a detailed description of the identity recognition system in multiple business scenarios provided by this application. Figure 5 , Figure 5 Another embodiment of the system for identity identification in multiple business scenarios provided by the present application includes:

[0131] An acquiring unit 501 is used to acquire an identity identification request sent by a business party, where the identity identification request includes an identity identification type and encrypted identity information;

[0132] The decryption unit 502 is used to determine the algorithm type specified by the service provider, and decrypt the encrypted identity information according to the algorithm type to obtain the identity information of the target user;

[0133] A first parsing unit 503, configured to parse the identity information according to the identity recognition type to obtain a first parsing result;

[0134] The second parsing unit 504 is used to obtain a second parsing result from a database according to the identity recognition type and the first parsing result. The database pre-stores identity information of a number of users, and the second parsing result is the identity information of the hard-parsed user;

[0135] A comparison unit 505, used to compare whether the first analysis result and the second analysis result are consistent;

[0136] A first assembling unit 506, configured to assemble the target user's identity recognition result information according to the second analysis result when the comparing unit 505 determines that the first analysis result and the second analysis result are consistent;

[0137] The first encryption unit 507 is used to encrypt the identity recognition result information according to the algorithm type and return the encrypted identity recognition result information to the business party.

[0138] Optionally, the system further includes:

[0139] The second assembling unit 508 is used to assemble the target user's identity recognition failure information according to the failure reason when the comparing unit 505 determines that the first parsing result and the second parsing result are inconsistent;

[0140] The second encryption unit 509 is used to encrypt the identity recognition failure information according to the algorithm type and return the encrypted identity recognition failure information to the business party.

[0141] Optionally, the second parsing unit 504 is specifically configured to:

[0142] querying in a database whether there is identity information related to the first parsing result according to the identity recognition type;

[0143] If so, determining the hard parsing result of the identity information related to the first parsing result in the database as the second parsing result;

[0144] If not, a second analysis result is obtained from the cooperation channel party according to the identity recognition type and the first analysis result.

[0145] Optionally, the first assembly unit 506 is specifically used for:

[0146] Determining the identification record of the target user according to the second analysis result;

[0147] Assemble the target user's identity recognition result information according to the second parsing result and the recognition record.

[0148] Optionally, the system further includes:

[0149] The verification unit 510 is used to perform integrity verification on the identity recognition request.

[0150] Optionally, the decryption unit 502 is specifically used for:

[0151] Determine the algorithm type specified by the business party based on the identifier carried in the identity identification request.

[0152] Optionally, the decryption unit 502 is further configured to:

[0153] The algorithm type specified by the business party is determined based on the business type associated with the identification request.

[0154] In this embodiment, the functions of each unit are the same as those described above. Figures 1 to 4 The steps in the method embodiment shown correspond to each other and will not be repeated here.

[0155] This application also provides a device for identity recognition in multiple business scenarios, please refer to Figure 6 , Figure 6 An embodiment of a device for identity identification in a multi-service scenario provided by the present application includes:

[0156] Processor 601, memory 602, input and output unit 603, bus 604;

[0157] The processor 601 is connected to the memory 602, the input and output unit 603 and the bus 604;

[0158] The memory 602 stores a program, and the processor 601 calls the program to execute the above method for identity recognition in any multi-service scenario.

[0159] The present application also relates to a computer-readable storage medium, on which a program is stored. When the program is run on a computer, the computer executes the method for identity identification in any of the above multi-business scenarios.

[0160] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0161] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0164] If the integrated unit is implemented in the form of a software functional unit 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 is 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 medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A method for identity recognition in a multi-service scenario, characterized in that: The method comprises: Obtaining an identity identification request sent by a business party, wherein the identity identification request includes an identity identification type and encrypted identity information; Determine the algorithm type specified by the business party, and decrypt the encrypted identity information according to the algorithm type to obtain the identity information of the target user; Parsing the identity information according to the identity recognition type to obtain a first parsing result; Acquire a second parsing result in a database according to the identity recognition type and the first parsing result, wherein identity information of a plurality of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user; comparing whether the first analysis result and the second analysis result are consistent; If yes, assembling the identity recognition result information of the target user according to the second analysis result; The identity recognition result information is encrypted according to the algorithm type, and the encrypted identity recognition result information is returned to the business party.

2. The method according to claim 1, characterized in that After comparing whether the first analysis result and the second analysis result are consistent, the method further includes: If not, assembling the target user's identity recognition failure information according to the failure reason; The identity recognition failure information is encrypted according to the algorithm type, and the encrypted identity recognition failure information is returned to the business party.

3. The method according to claim 1, characterized in that The acquiring a second parsing result in a database according to the identity recognition type and the first parsing result includes: querying in a database whether there is identity information related to the first parsing result according to the identity recognition type; If so, determining the hard parsing result of the identity information related to the first parsing result in the database as the second parsing result; If not, a second parsing result is obtained from the cooperation channel party according to the identity recognition type and the first parsing result.

4. The method according to claim 1, characterized in that The step of assembling the target user's identity recognition result information according to the second parsing result includes: Determining the identification record of the target user according to the second analysis result; Assemble the identity recognition result information of the target user according to the second parsing result and the recognition record.

5. The method according to claim 1, characterized in that Before determining the algorithm type specified by the business party and decrypting the encrypted identity information according to the algorithm type, the method further includes: Perform an integrity check on the identity identification request.

6. The method according to any one of claims 1 to 5, characterized in that Determine the algorithm type specified by the business party, including: The algorithm type specified by the business party is determined according to the identifier carried in the identity identification request.

7. The method according to any one of claims 1 to 5, characterized in that Determine the algorithm type specified by the business party, including: The algorithm type specified by the business party is determined according to the business type associated with the identity identification request.

8. A system for identity recognition in multiple business scenarios, characterized in that: The system comprises: An acquiring unit, configured to acquire an identity identification request sent by a business party, wherein the identity identification request includes an identity identification type and encrypted identity information; A decryption unit, used to determine the algorithm type specified by the service provider, and decrypt the encrypted identity information according to the algorithm type to obtain the identity information of the target user; A first parsing unit, configured to parse the identity information according to the identity recognition type to obtain a first parsing result; A second parsing unit, configured to obtain a second parsing result from a database according to the identity recognition type and the first parsing result, wherein identity information of a plurality of users is pre-stored in the database, and the second parsing result is identity information of the hard-parsed user; A comparing unit, used for comparing whether the first analysis result and the second analysis result are consistent; a first assembling unit, configured to assemble the identity recognition result information of the target user according to the second analysis result when the comparison unit determines that the first analysis result and the second analysis result are consistent; The first encryption unit is used to encrypt the identity recognition result information according to the algorithm type and return the encrypted identity recognition result information to the business party.

9. A device for identity recognition in multiple business scenarios, characterized in that: The device comprises: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a program stored thereon, wherein the program, when executed on a computer, performs the method according to any one of claims 1 to 7.

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