CN110557363A

CN110557363A - identity verification method, device and storage medium

Info

Publication number: CN110557363A
Application number: CN201910477693.6A
Authority: CN
Inventors: 张帆; 舒凯; 李跃红; 孙潞潞; 林洪优; 翟登磊
Original assignee: Beijing City Network Neighbor Technology Co Ltd
Current assignee: Beijing Urban Network Neighbor Information Technology Co Ltd; Beijing City Network Neighbor Technology Co Ltd
Priority date: 2019-06-03
Filing date: 2019-06-03
Publication date: 2019-12-10

Abstract

the embodiment of the application provides an identity verification method, an identity verification device and a storage medium, wherein the method comprises the following steps: acquiring a plurality of identity identifications corresponding to a user to be verified; wherein the plurality of identity identifications comprise unique identity identifications and non-unique identity identifications; determining the blacklist as a target blacklist associated with the user to be verified under the condition that any target non-unique blacklist identifier matched with the unique identity identifier does not exist in unique blacklist identifiers of the blacklist and at least one target non-unique blacklist identifier respectively matched with the non-unique identity identifier exists in non-unique blacklist identifiers of the blacklist; determining the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification; and carrying out identity verification on the user to be verified according to the matching degree.

Description

identity verification method, device and storage medium

Technical Field

The present application relates to the field of internet technologies, and in particular, to an identity verification method, an identity verification device, and a storage medium.

Background

With the rapid development of the communication network, more and more merchant users can register in the application platform, and the target commodity is released in a network form under the condition of successful registration, and at the moment, the application platform can acquire the unique identity corresponding to the merchant user. Considering the situation that the unqualified merchant user publishes the fake commodities, the method can judge whether the merchant user is a blacklist user or not in order to avoid economic loss of the unqualified merchant user for publishing the fake commodities to the buyer user.

In the prior art, if any one of the unique blacklist identifiers of the blacklist matches with the unique identity identifier of the merchant user, it may be determined that the merchant user is a blacklist user. However, when any one of the unique blacklist identifiers of the blacklist is not matched with the unique identity identifier of the merchant user, whether the merchant user is the blacklist user cannot be accurately identified.

disclosure of Invention

in view of the foregoing problems, embodiments of the present application provide an identity verification method, an identity verification device, and a storage medium, where, in a case that any one of the unique blacklist identifiers of the blacklist does not match with the unique identity identifier of the merchant user, a target blacklist associated with a user to be verified is obtained according to a non-unique blacklist identifier of the blacklist and a non-unique identity identifier of the user to be verified, so that a matching degree between the user to be verified and the target blacklist can be obtained, and then identity verification is performed on the user to be verified based on the matching degree, thereby avoiding a problem that whether the user to be verified is a blacklist user cannot be accurately identified in the prior art.

according to a first aspect of embodiments of the present application, there is provided an identity verification method, including:

Acquiring a plurality of identity identifications corresponding to a user to be verified; wherein the plurality of identities comprise a unique identity and a non-unique identity;

determining the blacklist as a target blacklist associated with the user to be verified under the condition that any target non-unique blacklist identifier matched with the unique identity identifier does not exist in the unique blacklist identifiers of the blacklist and at least one target non-unique blacklist identifier respectively matched with the non-unique identity identifier exists in the non-unique blacklist identifiers of the blacklist;

Determining the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification;

And carrying out identity verification on the user to be verified according to the matching degree.

optionally, the determining, according to the target non-unique blacklist identifier, a matching degree between the user to be verified and the target blacklist includes:

Acquiring the identification number of the target non-unique blacklist identification;

And determining the matching degree between the user to be verified and the target blacklist according to the identification number.

Acquiring the associated parameters of each target non-unique blacklist mark;

and determining the matching degree between the user to be verified and the target blacklist according to the correlation parameters.

optionally, before the determining, according to the target non-unique blacklist identifier, a matching degree between the user to be verified and the target blacklist, the method further includes:

Acquiring the priority of each target non-unique blacklist mark;

the determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier includes:

and acquiring the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification corresponding to the highest priority.

optionally, the obtaining, according to the target non-unique blacklist identifier corresponding to the highest priority, a matching degree between the user to be verified and the target blacklist includes:

Obtaining the matching degree to be determined between a target non-unique blacklist identification corresponding to the highest priority and a non-unique identity identification matched with the target non-unique blacklist identification corresponding to the highest priority;

judging whether the matching degree to be determined is greater than or equal to a first preset threshold value or not;

And taking the matching degree to be determined as the matching degree under the condition that the matching degree to be determined is greater than or equal to the first preset threshold value.

optionally, when the target blacklist includes a plurality of blacklists, the performing, according to the matching degree, identity verification on the user to be verified includes:

Acquiring blacklist grade parameters preset by each target blacklist;

acquiring verification parameters of the user to be verified according to the blacklist grade parameter corresponding to each target blacklist and the matching degree between each target blacklist and the user to be verified;

and carrying out identity verification on the user to be verified through the verification parameters.

acquiring the maximum matching degree from the matching degree corresponding to each target blacklist;

and carrying out identity verification on the user to be verified through the maximum matching degree.

Optionally, the performing identity verification on the user to be verified through the maximum matching degree includes:

determining the user to be checked as a blacklist user under the condition that the maximum matching degree is greater than or equal to a second preset threshold value; alternatively, the first and second electrodes may be,

And under the condition that the maximum matching degree is smaller than the second preset threshold value, determining that the user to be verified is a white list user.

according to a second aspect of the embodiments of the present application, there is provided an identity verification method, including:

the identity identification acquisition module is used for acquiring a plurality of identity identifications corresponding to the user to be verified; wherein the plurality of identity identifications comprise unique identity identifications and non-unique identity identifications;

a target blacklist obtaining module, configured to determine that a blacklist is a target blacklist associated with a user to be verified when any one of unique blacklist identifiers of the blacklist does not exist and a target non-unique blacklist identifier matching at least one of the non-unique blacklist identifiers of the blacklist exists;

The matching degree acquisition module is used for determining the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification;

and the identity verification module is used for verifying the identity of the user to be verified according to the matching degree.

Optionally, the matching degree obtaining module includes:

the identification data acquisition submodule is used for acquiring the identification number of the target non-unique blacklist identification;

And the first matching degree obtaining sub-module is used for determining the matching degree between the user to be verified and the target blacklist according to the identification number.

optionally, the matching degree obtaining module includes:

The associated parameter acquisition submodule is used for acquiring the associated parameter of each target non-unique blacklist mark;

and the second matching degree obtaining sub-module is used for determining the matching degree between the user to be verified and the target blacklist according to the associated parameters.

Optionally, the apparatus further comprises:

the priority acquisition module is used for acquiring the priority of each target non-unique blacklist identifier;

the matching degree obtaining module is used for obtaining the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification corresponding to the highest priority.

optionally, the matching degree obtaining module includes:

The matching degree to be determined obtaining sub-module is used for obtaining the matching degree to be determined between the target non-unique blacklist mark corresponding to the highest priority and the non-unique identity mark matched with the target non-unique blacklist mark corresponding to the highest priority;

the judging submodule is used for judging whether the matching degree to be determined is greater than or equal to a first preset threshold value;

And the third matching degree obtaining sub-module is used for taking the matching degree to be determined as the matching degree under the condition that the matching degree to be determined is greater than or equal to the first preset threshold value.

Optionally, in a case that the target blacklist includes a plurality of blacklists, the identity verification module includes:

The blacklist grade parameter acquisition submodule is used for acquiring a blacklist grade parameter preset by each target blacklist;

The verification parameter acquisition sub-module is used for acquiring the verification parameters of the user to be verified according to the blacklist grade parameters corresponding to each target blacklist and the matching degree between each target blacklist and the user to be verified;

And the first identity verification submodule is used for verifying the identity of the user to be verified through the verification parameters.

The maximum matching degree obtaining sub-module is used for obtaining the maximum matching degree from the matching degree corresponding to each target blacklist;

And the second identity verification submodule is used for verifying the identity of the user to be verified through the maximum matching degree.

optionally, the second identity verification sub-module is configured to determine that the user to be verified is a blacklist user when the maximum matching degree is greater than or equal to a second preset threshold; alternatively, the first and second electrodes may be,

According to a third aspect of the embodiments of the present application, there is provided an identity verification apparatus, comprising a processor and a memory, wherein,

The processor executes the computer program code stored in the memory to implement the steps of the identity verification method described herein.

according to a fourth aspect of embodiments herein, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the identity verification method described herein.

The embodiment of the application has the following advantages:

The method comprises the steps of obtaining a plurality of identity identifications corresponding to a user to be verified; wherein the plurality of identity identifications comprise unique identity identifications and non-unique identity identifications; determining the blacklist as a target blacklist associated with the user to be verified under the condition that any target non-unique blacklist identifier matched with the unique identity identifier does not exist in the unique blacklist identifiers of the blacklist and at least one target non-unique blacklist identifier respectively matched with the non-unique identity identifier exists in the non-unique blacklist identifiers of the blacklist; determining the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification; and carrying out identity verification on the user to be verified according to the matching degree.

therefore, the method and the device can judge whether the target non-unique blacklist identifier respectively matched with at least one non-unique identity identifier exists in the non-unique blacklist identifiers of the blacklist under the condition that any one of the unique blacklist identifiers of the blacklist is not matched with the unique identity identifier, so that the target blacklist associated with the user to be verified is obtained from the blacklist through the non-unique identity identifier. In consideration of the fact that the matching degrees between different target blacklists and the user to be verified are different, the target blacklist with the higher matching degree has a larger influence on the identity verification result, and the target blacklist with the lower matching degree has a smaller influence on the identity verification result, so that the user verification according to the matching degree has higher reliability, and the accuracy of the user verification is improved.

drawings

FIG. 1 is a flow chart of the steps of an embodiment of an identity verification method of the present application;

FIG. 2 is a flow chart illustrating steps in an alternative embodiment of an identity verification method of the present application;

FIG. 3 is a flow chart illustrating steps of an alternative embodiment of an identity verification method of the present application;

FIG. 4 is a flow chart illustrating steps of an alternative embodiment of an identity verification method of the present application;

FIG. 5 is a block diagram of an embodiment of an identity verification apparatus according to the present application;

FIG. 6 is a block diagram of an alternative embodiment of an identity verification apparatus of the present application;

Fig. 7 is a schematic hardware structure diagram of an identity verification apparatus according to another embodiment of the present application;

fig. 8 is a schematic hardware structure diagram of an identity verification apparatus according to another embodiment of the present application.

Detailed Description

in order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.

First, an application scenario of the present application is described, and the present application may be applied to an identity verification scenario, in which a merchant user registers in an X1 application platform using an IP (Internet Protocol Address) Address Y and a user mobile phone number T1, and issues a target product if the registration is successful, and a general buyer user may evaluate the target product after purchasing the target product and/or complaint the merchant user if the target product is a poor product, so that the X1 application platform may use the merchant user as a blacklist and the IP Address Y1 and the user mobile phone number T1 as identifiers of the blacklist according to an evaluation result and/or complaint information. However, in a general case, the merchant user may further use the IP address Y and the user mobile phone number T2 to continue to register in the X1 application platform, where the user mobile phone number is a unique identity and the IP address is a non-unique identity, and since the user mobile phone number T2 is different from the user mobile phone number T1, the X1 application platform cannot recognize that the merchant user is a blacklist user.

In order to solve the problem, because the identity usually includes a unique identity and a non-unique identity, the method and the device for verifying the blacklist can judge whether a target non-unique blacklist identity respectively matched with at least one non-unique identity exists in the non-unique blacklist of the blacklist under the condition that any one of the unique blacklist identities of the blacklist is not matched with the unique identity, so that the target blacklist related to the user to be verified is obtained from the blacklist through the non-unique identity. In consideration of the fact that the matching degrees between different target blacklists and the user to be verified are different, the target blacklist with the higher matching degree has a larger influence on the identity verification result, and the target blacklist with the lower matching degree has a smaller influence on the identity verification result, so that the user verification performed according to the matching degrees has higher reliability, and the accuracy of the user verification is improved.

The present application will be described in detail with reference to specific examples.

referring to fig. 1, a flowchart illustrating steps of an embodiment of an identity verification method of the present application is shown, which may specifically include the following steps:

step 101, acquiring a plurality of identity identifications corresponding to a user to be verified; wherein the plurality of identities comprise a unique identity and a non-unique identity.

in this embodiment of the application, the unique identifier may be a user phone number, a user identification card number, a user face image, a user fingerprint image, and the like, and the non-unique identifier may be a Media Access Control (MAC) address, a user account, a payment code, an IP address, a cookie identifier, posting information, and the like, which are only examples, and this application is not limited thereto.

because the application can be applied to the current application platform used by the user to be verified, in a possible implementation manner, a plurality of identity identifiers of the user to be verified in the current application platform can be obtained, namely the obtained identity identifiers are operated (such as operations of registration, login, posting or access) according to the historical behaviors of the user to be verified in the current application platform; in another possible implementation manner, the user to be verified may have historical behavior operations in different application platforms respectively, and therefore, different application platforms may obtain a plurality of initial identifiers of the user to be verified in corresponding application platforms respectively, where the plurality of initial identifiers may include an initial unique identifier and an initial non-unique identifier, and since the initial unique identifiers in different application platforms may have an association relationship, that is, a certain initial unique identifier in one application platform is the same as a certain unique initial identifier in another application platform, the application may use the initial unique identifiers having an association relationship in different application platforms and the initial non-unique identifiers associated with the initial unique identifier as the plurality of identifiers in this step, and after acquiring the plurality of identity identifications, dividing the plurality of identity identifications into unique identity identifications and non-unique identity identifications.

step 102, under the condition that any target non-unique blacklist mark matched with the unique identity mark does not exist in the unique blacklist marks of the blacklist and at least one target non-unique blacklist mark respectively matched with the non-unique identity mark exists in the non-unique blacklist marks of the blacklist, determining the blacklist as a target blacklist associated with the user to be verified.

in this step, it can be determined whether any one of the unique blacklist identifiers of the blacklist matches the unique identity identifier, and under the condition that any one of the unique blacklist identifiers of the blacklist matches the unique identity identifier, it is determined that the user to be verified is the blacklist user, so that a subsequent process of obtaining the matching degree is not required, and further, the waste of computing resources is avoided; under the condition that any one of the unique blacklist identifications of the blacklist is not matched with the unique identity identification, judging whether a target non-unique blacklist identification respectively matched with at least one non-unique identity identification exists in the non-unique blacklist identification of the blacklist, thus under the condition that the target non-unique blacklist identification respectively matched with at least one non-unique identity identification does not exist in the non-unique blacklist identification of the blacklist, determining that the blacklist is not a target blacklist associated with the user to be verified; and under the condition that target non-unique blacklist identifications respectively matched with at least one non-unique identity identification exist in the non-unique blacklist identifications of the blacklist, determining the blacklist as a target blacklist associated with the user to be verified.

In the embodiment of the application, a blacklist can be obtained from a blacklist map, and the blacklist map comprises a corresponding relation between a blacklist and a blacklist identity corresponding to the blacklist; the blacklist is a list acquired from a plurality of application platforms; the blacklist identity includes a unique blacklist identity and a non-unique blacklist identity. It should be noted that, since the present application mainly aims to identify the blacklist user, the constructed blacklist map includes the blacklist. Of course, in another alternative embodiment, the list map in the present application may also include a white list, which is not limited in the present application.

Illustratively, the multiple application platforms may be different application platforms under the same company (e.g., 58 city under 58 colleagues, catch-up nets, Chinese talent nets, live guests, 58 home, transfer and 58 city movies, etc.). In order to make the coverage information of the blacklist in the shortlist map wider and thus make the identification accuracy of the blacklist user higher, the plurality of application platforms may further include application platforms in an industry alliance (such as 58-aggregator group, ariiba group, kyoto group, public security bureau, consumer association, and the like), and the above examples are only illustrative, and the present application is not limited thereto.

Alternatively, the list map may be constructed by:

And S11, obtaining a blacklist sample from the list samples included by the plurality of application platforms.

In this step, each application platform has a corresponding list sample, and each application platform can perform list screening according to a corresponding preset blacklist condition to obtain a blacklist sample and a white list sample in each application platform. Therefore, the method and the device can execute subsequent steps on each blacklist sample in all the application platforms, so that the identity identification samples belonging to the same blacklist are associated to the same blacklist, thereby realizing the association of the identity identifications of the same blacklist in different application platforms, the association of the identity identifications of the same blacklist in different terminals and the like.

each application platform can be provided with a corresponding preset blacklist condition, so that a list sample in each application platform is obtained, and an identity sample corresponding to the list sample is obtained, wherein the identity sample comprises: the method comprises the steps of obtaining a list sample, wherein the list sample comprises a unique identity identification sample (a user mobile phone number, a user identity card number, a user face image, a user fingerprint image and the like) and/or a non-unique identity identification sample (a MAC address, a user account number, a payment code, an IP address, a cookie identification, posting information and the like), judging whether the list sample meets a preset blacklist condition or not based on the identity identification sample, determining the list sample to be the blacklist sample under the condition that the list sample meets the preset blacklist condition, and determining the list sample to be the white list sample under the condition that the list sample does not meet the preset blacklist condition.

further, the preset blacklist condition includes at least one of: the list sample does not complete user authentication (such as real name authentication or mobile phone authentication); the registration time of the list sample is less than or equal to the preset time (such as 5 months); the list sample does not release commodity information in the registration time period; historical commodity information issued by the list sample does not belong to the preset commodity information category; the list sample has complaint records, and the complaint records are determined to pass the complaint examination; and the number of complaints of the list sample in a preset time period is greater than or equal to the preset number.

for example, in a case that the preset blacklist condition includes that the list sample does not complete user authentication, since at least one unique identity sample generally exists in an authenticated user, this step may determine whether at least one unique identity sample exists in the identity sample, and determine that the list sample is a blacklist sample in a case that the unique identity sample does not exist in the identity sample, and determine that the list sample is a whitelist sample in a case that at least one unique identity sample exists in the identity sample.

Under the condition that the preset blacklist condition includes that the registration time length of the list sample is less than or equal to the preset time length, the list unique identity matched with the unique identity sample can be obtained from a registration time length list, the registration time length list includes registration time lengths corresponding to different list unique identity identifiers, in this way, the registration time length of the list unique identity matched with the unique identity sample can be determined to be the registration time length of the list sample, and therefore whether the registration time length is less than or equal to the preset time length or not is judged.

under the condition that the preset blacklist condition comprises that the list sample does not release commodity information in the registration time period, because the historical commodity information released by the list sample is generally bound with the unique identity sample, whether the historical commodity information which has a binding relationship with the unique identity sample exists or not can be judged, and if the historical commodity information which has a binding relationship with the unique identity sample exists, the commodity information released by the list sample in the registration time period is determined; and if the historical commodity information which has a binding relationship with the unique identity sample does not exist, determining that the list sample does not release the commodity information within the registration time period.

Under the condition that the preset blacklist condition includes that the historical commodity information issued by the list sample does not belong to the preset commodity information category, the historical commodity information issued by the list sample is usually bound with the unique identity sample, so that the historical commodity information bound with the list sample can be obtained according to the unique identity sample, and the commodity type information is extracted from the historical commodity information, so that whether the commodity type information belongs to the preset commodity information category or not is judged. If the commodity type information extracted from any historical commodity information does not belong to the preset commodity information category, the list sample can be determined to be a blacklist sample.

Under the condition that the preset blacklist condition includes that a complaint record exists in a list sample and the identification result of the complaint record is that the complaint record passes complaint audit, a complaint list can be obtained firstly, wherein the complaint list includes a plurality of list unique identity identifications and the identification result of the list unique identity, so that whether a target list unique identity matched with the unique identity sample exists in the list unique identity identifications is judged, and under the condition that the target list unique identity matched with the unique identity sample exists in the list unique identity, the identification result corresponding to the target list unique identity is the identification result of the list sample.

Under the condition that the preset blacklist condition includes that the number of complaints of the list sample in the preset time period is greater than or equal to the preset number of complaints, similarly, a complaint list can be obtained firstly, the complaint list also includes the number of complaints corresponding to the plurality of list unique identity identifications respectively, in this way, whether a target list unique identity matched with the unique identity sample exists in the plurality of list unique identity identifications is judged, and under the condition that the target list unique identity matched with the unique identity sample exists in the plurality of list unique identity identifications, the number of complaints corresponding to the target list unique identity is taken as the number of complaints of the list sample.

Therefore, the blacklist sample can be obtained through the preset blacklist condition, and the screening process can be referred to under the condition that the preset blacklist condition includes multiple conditions, which is not described in detail.

S12, acquiring a first identity identification set corresponding to the blacklist sample; the first identity identification set comprises a unique blacklist identification sample of the blacklist sample and a non-unique blacklist identification sample of the blacklist sample.

In the embodiment of the present application, there are usually a plurality of corresponding identity samples in the list sample, and the identity samples exist in pairs. The log information can be collected through the application platform, and after the log information is cleaned, identity identification samples appearing in pairs are obtained from the cleaned log information. Therefore, the method and the device can generate the identity set corresponding to the list sample according to the identity samples appearing in pairs. For example, if a user registers in an application platform, under the condition that a mobile phone number and a user account of the user are obtained, the mobile phone number and the user account of the user can be considered to belong to the same user, and at this time, the mobile phone number and the user account of the user can be used as identity samples in an identity set of the user. In summary, after the identity identifier set corresponding to each list sample is obtained, the blacklist sample can be obtained from the list sample, and the first identity identifier set corresponding to the blacklist sample can be obtained.

Further, in the case that the plurality of application platforms include an application platform of an industry alliance, an alliance block chain connected to the plurality of application platforms may be first constructed, so that each application platform transmits corresponding list query information to the alliance block chain by using a cross-chain technique of the block chain, and in order to trace back a data source, the application may transmit the list query information according to a preset data format, for example, the preset data format is "data source + data information", the data information may include first data and second data, the first data is a list type, the second data is identity information, for example, the list type is a blacklist type or a whitelist type, the identity information is { user name, user identification number, user mobile phone number, organization code card, enterprise name, credit log record }, therefore, the list sample and the identity set corresponding to the list sample are not sent to the alliance block chain, but the list sample and the identity set corresponding to the list sample are inquired in the corresponding application platform through the list inquiry information, so that the information safety is ensured. In addition, in order to further improve the information security, the method and the device can also encrypt the list query information, for example, the list query information is encrypted through a hash algorithm, so that the list query information is difficult to tamper. In this way, the block chain of alliances in the application can obtain list samples of a plurality of application platforms of an industry alliance and identity identification sets corresponding to the list samples according to the list query information.

In order to enable a plurality of application platforms to use the federation blockchain in a specification manner, an intelligent contract of the federation blockchain may be formulated by the plurality of application platforms together, and the intelligent contract of the federation blockchain is to be executed automatically. By adopting the blockchain technology, the list map has the characteristics of decentralization, collective maintenance and non-falsification of time sequence data. It should be noted that, in the subsequent step, the plurality of application platforms may share the list atlas through the federation blockchain, and for other application platforms except the plurality of application platforms, the payment is needed, and the related payment may be made by the plurality of application platforms together.

S13, judging whether at least one target list sample associated with the blacklist sample exists in the list samples included in the plurality of application platforms; and at least one identical identity identification sample exists between the second identity identification set corresponding to the target list sample and the unique identity identification sample of the blacklist sample. The second identity set comprises a unique identity sample corresponding to the target list sample and a non-unique identity sample corresponding to the target list sample.

performing S14 and S16 in the presence of at least one target list sample associated with the blacklist sample;

in case there is no at least one target blacklist sample associated with the blacklist sample, performing S15 and S16.

S14, merging the blacklist sample and the at least one target list sample into a blacklist included in the list map, and merging the first identity identification set and the second identity identification set to obtain the blacklist identity of the blacklist.

In this step, the blacklist id of the blacklist may include a unique blacklist id sample of the blacklist sample, a non-unique blacklist id sample of the blacklist sample, a unique id sample corresponding to the at least one target name list sample, and a non-unique id sample corresponding to the at least one target name list sample. For example, the identity (i.e., the MAC address WW, the mobile phone number identifier RR, and the User account D1) of a blacklist User1 is obtained in the P application platform, and the identity (i.e., the MAC address WW, the mobile phone number identifier RR, and the User account D2) of a list User2 is obtained in the Q application platform, since the mobile phone number identifiers of the User1 and the User2 are respectively the same, in the case that the User1 is a blacklist, the User1 and the User2 may be used as the same blacklist, and the MAC address WW, the mobile phone number identifier RR, the User account D1, and the User account D2 are associated with the same blacklist, that is, the MAC address, the User account D1, and the User account D2 are used as non-unique blacklist identifiers of the same blacklist, and the mobile phone number identifier RR is used as a unique blacklist identifier of the same blacklist.

S15, taking the blacklist sample as a blacklist included in the list map, and taking the first identity identification set as the blacklist identity identification of the blacklist.

In this step, since the identity set corresponding to each blacklist sample and the unique identity sample of the blacklist sample do not have at least one identical identity sample, the blacklist sample may be considered as an individual blacklist, and the blacklist identity includes a unique blacklist identifier and a non-unique blacklist identifier.

S16, constructing the business form map according to the blacklist and the blacklist identity of the blacklist.

in this step, the list map may include identity clusters corresponding to each blacklist, and specifically, in this step, the blacklist identities of the blacklist may be connected to form a mesh structure, and the blacklist identities of the blacklist may be bound to the blacklist by using a graph mining algorithm. Of course, the list map in the present application may further include an identity cluster corresponding to the white list.

It should be noted that, according to the above manner, after the list map is obtained for the first time, a new sample of the list can be collected. If the list map is obtained again in the above manner each time, the processing pressure is large. In order to solve the problem, after the list map is constructed for the first time, a new list sample can be obtained according to the current period, a new list map is obtained according to the new list sample, the new list map is combined into the list map constructed in the previous period to obtain an updated list map, specifically, a graph x component of spark can be called, the new list map is combined into the list map constructed in the previous period, and the graph x component updates the list map by calling a community mining algorithm or a graph mining algorithm.

In addition, if the list map is constructed by the federation block, an external query interface may be set in the federation block chain, so that the plurality of application platforms and other platforms except the plurality of application platforms can acquire the list map through the external query interface, and perform identity verification through the list map. In addition, when abnormal query is detected by the block chain of the alliance, alarm prompt can be performed to timely process the abnormal query problem, for example, the application platform with the abnormal query is deleted from the block chain of the alliance, so that data security is improved.

In addition, if a list map is constructed through the federation block chains, the current application platform needs to acquire the list map from the federation block chains, so that the application needs to send a map acquisition instruction to the federation block chains corresponding to the multiple application platforms; the map obtaining instruction is used for indicating that the list map is obtained from the alliance block chain, the map obtaining instruction comprises a platform identifier of a current application platform, therefore, after the alliance block chain receives the map obtaining instruction, whether the current application platform belongs to any application platform in alliances can be determined according to the platform identifier, and under the condition that the current application platform belongs to any application platform in alliances, the alliance block chain responds to the map obtaining instruction to send the list map to the current application platform; and under the condition that the current application platform does not belong to any application platform in the alliance, sending a payment request instruction to the current application platform, so that the current application platform carries out payment to the alliance block chain after receiving the payment request instruction, and thus, the alliance block chain can complete operation according to the payment and send the list atlas to the current application platform. In summary, after receiving the list map sent by the alliance block chain, the present application may obtain a target blacklist having an association relationship with the user to be verified based on the list map.

Therefore, by constructing the list map, the target blacklist having the association relation with the user to be verified can be obtained based on the list map. The blacklist identity corresponding to the blacklist in the constructed list map can include an identity associated with the blacklist in different application platforms, so that the coverage range of the blacklist identity of the blacklist is wide, and therefore, in the subsequent steps, based on the blacklist identity with the wide coverage range, the matching degree between the user to be verified and the target blacklist can be accurately obtained, and further identity verification is performed on the user to be verified based on the matching degree.

Step 103, determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier.

for example, when the terminal used by the user to be verified is a public terminal, and an MAC address corresponding to a certain blacklist is consistent with an MAC address of the public terminal in the list map, if it is determined that the user to be verified is a blacklist user, since the user corresponding to the certain blacklist and the user to be verified both use the public terminal together, but not the same user, the identity verification result of the user to be verified is incorrect. In order to solve the problem, the matching degree between the user to be verified and the target blacklist is obtained, so that the target blacklist which is higher in matching degree with the user to be verified has a larger influence on the identity verification result of the user to be verified, and the target blacklist which is lower in matching degree with the user to be verified has a smaller influence on the identity verification result of the user to be verified.

and 104, performing identity verification on the user to be verified according to the matching degree.

In the embodiment of the present application, the identity of the user to be verified may be verified in the following manner:

in a first mode, under the condition that the target blacklist comprises a single blacklist, whether the matching degree is greater than or equal to a preset matching threshold value can be judged; under the condition that the matching degree is greater than or equal to a preset matching threshold value, determining that the user to be verified is a blacklist user; and under the condition that the matching degree is smaller than a preset matching threshold, determining that the user to be verified is a white list user.

In a second mode, under the condition that the target blacklist comprises a plurality of blacklists, because the blacklist grades corresponding to each blacklist in the blacklist map are different, the blacklist grade parameter can be different grades of preset blacklists, moreover, the blacklist with a higher blacklist grade has a larger influence on the identity verification result, and the blacklist with a lower blacklist grade has a smaller influence on the identity verification result, the method can firstly obtain the blacklist grade parameter preset by each target blacklist; then, according to the blacklist grade parameter corresponding to each target blacklist and the matching degree between each target blacklist and the user to be verified, obtaining the verification parameter of the user to be verified, namely calculating the product of the blacklist grade parameter corresponding to each target blacklist and the matching degree between each target blacklist and the user to be verified, obtaining the blacklist evaluation value corresponding to each target blacklist, and calculating the sum value between the blacklist evaluation values corresponding to each target blacklist to obtain the verification parameter of the user to be verified; and performing identity verification on the user to be verified through the verification parameters, wherein the probability that the user to be verified is a blacklist user is higher if the verification parameters are larger, and the probability that the user to be verified is the blacklist user is lower if the verification parameters are smaller. Therefore, in a possible implementation manner, it may be determined whether the verification parameter is greater than or equal to the preset verification value, and when the verification parameter is greater than or equal to the preset verification value, it is determined that the user to be verified is a blacklist user, and when the verification parameter is less than the preset verification value, it is determined that the user to be verified is a whitelist user; in another possible implementation manner, a preset user initial value may be obtained, a difference between the preset user initial value and a verification parameter is calculated, a white list evaluation parameter of a user to be verified is obtained, whether the white list evaluation parameter is greater than or equal to a preset evaluation value is judged, the user to be verified is determined to be a white list user when the white list evaluation parameter is greater than or equal to the preset evaluation value, and the user to be verified is determined to be a black list user when the white list evaluation parameter is less than the preset evaluation value.

In a third mode, under the condition that the target blacklist includes a plurality of blacklists, considering the condition that the matching degree between the user to be verified and a certain target blacklist is high, at this time, the user to be verified and the certain target blacklist can be determined to be the same user, and therefore the user to be verified is determined to be a blacklist user. Specifically, the maximum matching degree may be obtained from the matching degree corresponding to each target blacklist; performing identity verification on the user to be verified through the maximum matching degree, further judging whether the maximum matching degree is greater than or equal to a second preset threshold, and determining that the user to be verified is a blacklist user under the condition that the maximum matching degree is greater than or equal to the second preset threshold; or, determining that the user to be verified is a white list user under the condition that the maximum matching degree is smaller than the second preset threshold value.

by adopting the method, the blacklist can be obtained from the list samples included by the plurality of application platforms, and thus, the identity identification usually comprises the unique identity identification and the non-unique identity identification, so that the method can judge whether the target non-unique blacklist identification respectively matched with at least one non-unique identity identification exists in the non-unique blacklist identification of the blacklist under the condition that any one of the unique blacklist identifications of the blacklist is not matched with the unique identity identification, and the target blacklist associated with the user to be verified is obtained from the blacklist through the non-unique identity identification. In consideration of the fact that the matching degrees between different target blacklists and the user to be verified are different, the target blacklist with the higher matching degree has a larger influence on the identity verification result, and the target blacklist with the lower matching degree has a smaller influence on the identity verification result, so that the user verification according to the matching degree has higher reliability, and the accuracy of the user verification is improved.

referring to fig. 2, which is a flowchart illustrating steps of an alternative embodiment of the identity verification method according to the present application, the determining, according to the target non-unique blacklist identifier, a matching degree between the user to be verified and the target blacklist in step 103 may include:

And step 1031, acquiring the identification number of the target non-unique blacklist identification.

Illustratively, the non-unique identifiers of the user to be verified include R1, R2, R3 and R4, and the non-unique blacklist identifiers corresponding to the blacklist include R1, R2, R5 and R6, then it may be determined that the same identifier includes R1 and R2, at this time, it may be determined that the same identifiers R1 and R2 are target non-unique blacklist identifiers, so that the identifier number of the target non-unique blacklist identifiers is 2.

it should be noted that the non-unique identity identifier may further include at least one posting information, and therefore, a similarity between each posting information and the specified posting information of the blacklist may be calculated, and the specified posting information is labeled with a black post identifier, so that, when the similarity is greater than or equal to a preset similarity, it may be determined that the posting information matches with the specified posting information of the blacklist, and at this time, the specified posting information is the target non-unique blacklist identifier; in a case that the similarity is smaller than the preset similarity, it may be determined that the posting information does not match the specified posting information of the blacklist, and at this time, the specified posting information is not a target non-unique blacklist identifier.

Step 1032, determining the matching degree between the user to be verified and the target blacklist according to the number of the identifiers.

The larger the number of the identifiers is, the more likely the user to be verified and the target blacklist belong to the same user, so that the matching degree between the user to be verified and the target blacklist is higher; the smaller the number of the identifiers is, the less likely the user to be verified and the target blacklist belong to the same user, and thus the lower the matching degree between the user to be verified and the target blacklist is. Therefore, the matching degree in the present application is directly compared with the number of identifiers, for example, the number of identifiers is used as the matching degree between the user to be verified and the target blacklist, or the matching degree between the user to be verified and the target blacklist is obtained after the number of identifiers is normalized.

Referring to fig. 3, which is a flowchart illustrating steps of an alternative embodiment of the identity verification method according to the present application, the determining, according to the target non-unique blacklist identifier, a matching degree between the user to be verified and the target blacklist in step 103 may include:

Step 1033, obtaining the associated parameter of each target non-unique blacklist identifier.

In the embodiment of the application, the association parameters may be set for different non-unique blacklist identifiers in advance, so that the association parameters of each target non-unique blacklist identifier may be obtained in this step. For example, the association parameter corresponding to the posting information may be set to W1, the association parameter corresponding to the MAC address may be set to W2, the association parameter corresponding to the user account is set to W3, and W1 > W2 > W3, so that the influence degrees of different non-unique blacklist identifiers on the matching degree may be different, and the matching degree obtained in the subsequent step is more accurate.

step 1034, determining the matching degree between the user to be verified and the target blacklist according to the correlation parameters.

In a possible implementation manner, the step may calculate a sum value of each associated parameter to obtain a matching degree between the user to be verified and the target blacklist; in another possible implementation manner, in this step, after the sum value of each associated parameter is calculated, the sum value is normalized to obtain the matching degree between the user to be verified and the target blacklist, which is only an example, and this is not limited in this application.

Referring to fig. 4, which is a flowchart illustrating steps of an alternative embodiment of the identity verification method according to the present application, before determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier in step 103, the method may further include:

And 105, acquiring the priority of each target non-unique blacklist identifier.

The priorities of different non-unique blacklist identifications can be preset, so that the priority of the target non-unique blacklist identification can be obtained in the step. For example, if the non-unique blacklist identifier includes a MAC address, a user account, an IP address and posting information, the priority of the non-unique blacklist identifier is from high to low: the posting information, the MAC address, the user account and the IP address have higher priority than the MAC address when the target non-unique blacklist mark is the posting information and the MAC address.

in this case, step 103 is: and acquiring the matching degree between the user to be verified and the target blacklist according to the target non-uniqueness blacklist identification corresponding to the highest priority.

In the embodiment of the application, the matching degree to be determined between the target non-unique blacklist identifier corresponding to the highest priority and the non-unique identity identifier matched with the target non-unique blacklist identifier corresponding to the highest priority can be obtained firstly; then judging whether the matching degree to be determined is greater than or equal to a first preset threshold value; finally, under the condition that the matching degree to be determined is greater than or equal to the first preset threshold, taking the matching degree to be determined as the matching degree; and under the condition that the matching degree to be determined is smaller than the first preset threshold, obtaining the matching degree between the user to be verified and the target blacklist according to the method shown in any one of fig. 2 or fig. 3.

Continuing with the example in step 105 as an example, if the target non-unique blacklist identifier is posting information and a MAC address, and the priority of the posting information is higher than the priority of the MAC address, this step may obtain a to-be-determined matching degree between the posting information and specified posting information of the target blacklist, where the specified posting information is marked with a black post identifier, and thus, when the to-be-determined matching degree is greater than or equal to a preset matching degree, it may be determined that the to-be-determined matching degree is a matching degree between the to-be-verified user and the target blacklist. It can be seen that, because the target non-unique blacklist identifier with a higher priority has a higher influence on the verification result, and the matching degree to be determined between the target non-unique blacklist identifier with the highest priority and the non-unique identity identifier matched with the target non-unique blacklist identifier corresponding to the highest priority is higher, the influence of other target non-unique blacklist identifiers except for the highest priority on the matching degree can be ignored.

It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.

Referring to fig. 5, a block diagram of an embodiment of an identity verification apparatus 500 of the present application is shown, which may specifically include the following modules:

An identity obtaining module 501, configured to obtain multiple identities corresponding to a user to be verified; wherein the plurality of identity identifiers comprise a unique identity identifier and a non-unique identity identifier;

A target blacklist obtaining module 502, configured to determine that a blacklist is a target blacklist associated with a user to be verified when any target non-unique blacklist identifier matching the unique identity identifier does not exist in a unique blacklist identifier of the blacklist and at least one target non-unique blacklist identifier respectively matching the non-unique identity identifier exists in the non-unique blacklist identifier of the blacklist;

a matching degree obtaining module 503, configured to determine, according to the target non-unique blacklist identifier, a matching degree between the user to be verified and the target blacklist;

and the identity verification module 504 is configured to perform identity verification on the user to be verified according to the matching degree.

Optionally, the matching degree obtaining module 503 includes:

optionally, the matching degree obtaining module 503 includes:

referring to fig. 6, a block diagram of an embodiment of an identity verification apparatus 500 of the present application is shown, where the apparatus 500 further includes:

a priority obtaining module 505, configured to obtain a priority of each target non-unique blacklist identifier;

the matching degree obtaining module 503 is configured to obtain a matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier corresponding to the highest priority.

Optionally, the matching degree obtaining module 503 includes:

optionally, the identity verification module 504 includes:

optionally, in a case that the target blacklist includes a plurality of blacklists, the identity verification module 504 includes:

for the specific implementation process of the above device embodiment, reference may be made to the method embodiment, which is not described herein again.

The present application further provides a non-volatile readable storage medium, where one or more modules (programs) are stored in the storage medium, and when the one or more modules are applied to a terminal device, the one or more modules may cause the terminal device to execute instructions (instructions) of method steps in the present application.

fig. 7 is a schematic diagram of a hardware structure of an identity verification apparatus according to an embodiment of the present application. As shown in fig. 7, the identity verification apparatus may comprise an input device 70, a processor 71, an output device 72, a memory 73 and at least one communication bus 74. The communication bus 74 is used to enable communication connections between the elements. The memory 73 may comprise a high speed RAM memory, and may also include a non-volatile memory NVM, such as at least one disk memory, in which various programs may be stored for performing various processing functions and implementing the method steps of the present embodiment.

Alternatively, the processor 71 may be implemented by, for example, a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and the processor 71 is coupled to the input device 70 and the output device 72 through a wired or wireless connection.

alternatively, the input device 70 may include a variety of input devices, such as at least one of a user-oriented user interface, a device-oriented device interface, a software-programmable interface, a camera, and a sensor. Optionally, the device interface facing the device may be a wired interface for data transmission between devices, or may also be a hardware plug-in interface (e.g., a USB interface, a serial port, etc.) for data transmission between devices; optionally, the user-oriented user interface may be, for example, a user-oriented control key, a voice input device for receiving voice input, and a touch sensing device (e.g., a touch screen with touch sensing function, a touch pad, etc.) for receiving user touch input; optionally, the programmable interface of the software may be, for example, an entry for a user to edit or modify a program, such as an input pin interface or an input interface of a chip; optionally, the transceiver may be a radio frequency transceiver chip with a communication function, a baseband processing chip, a transceiver antenna, and the like. An audio input device such as a microphone may receive voice data. The output device 72 may include a display, a sound, or the like.

in this embodiment, the processor of the identity verification apparatus includes a function for executing each module in the identity verification apparatus, and specific functions and technical effects are as described in the above embodiments, which are not described herein again.

Fig. 8 is a schematic hardware structure diagram of an identity verification apparatus according to another embodiment of the present application. FIG. 8 is a specific embodiment of FIG. 7 in an implementation. As shown in fig. 8, the identity verification apparatus of the present embodiment includes a processor 81 and a memory 82.

the processor 81 executes the computer program code stored in the memory 82 to implement the identity verification method of fig. 1 to 4 in the above embodiments.

the memory 82 is configured to store various types of data to support operation in the identity verification method. Examples of such data include instructions for any application or method operating on the identity verification device, such as messages, pictures, videos, and the like. The memory 82 may include a Random Access Memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

Optionally, the processor 81 is provided in the processing assembly 80. The identity verification apparatus may further include: a communication component 83, a power component 84, a multimedia component 85, an audio component 86, an input/output interface 87 and/or a sensor component 88. The components and the like specifically included in the identity verification device are set according to actual requirements, and this embodiment does not limit this.

the processing component 80 generally controls the overall operation of the identity verification device. The processing component 80 may include one or more processors 81 to execute instructions to perform all or some of the steps of the methods of fig. 1-4 described above. Further, the processing component 80 may include one or more modules that facilitate interaction between the processing component 80 and other components. For example, the processing component 80 may include a multimedia module to facilitate interaction between the multimedia component 85 and the processing component 80.

The power supply component 84 provides power to the various components of the identity verification device. The power components 84 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the identity verification device.

The multimedia component 85 includes a display screen that provides an output interface between the identity verification device and the user. In some embodiments, the display screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

the audio component 86 is configured to output and/or input audio signals. For example, the audio component 86 includes a Microphone (MIC). The received audio signal may further be stored in the memory 82 or transmitted via the communication component 83. In some embodiments, audio assembly 86 also includes a speaker for outputting audio signals.

The input/output interface 87 provides an interface between the processing component 80 and peripheral interface modules, which may be click wheels, buttons, etc. These buttons may include, but are not limited to: a volume button, a start button, and a lock button.

the sensor assembly 88 includes one or more sensors for providing various aspects of status assessment for the identity verification device. For example, the sensor assembly 88 may detect the open/closed status of the identity verification device, the relative positioning of the components, the presence or absence of user contact with the identity verification device. The sensor assembly 88 may include a proximity sensor configured to detect the presence of a nearby object in the absence of any physical contact. In some embodiments, the sensor assembly 88 may also include a camera or the like.

The communication component 83 is configured to facilitate communication between the identity verification device and other equipment in a wired or wireless manner. The identity verification device may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof.

From the above, the communication component 83, the audio component 86, the input/output interface 87 and the sensor component 88 referred to in the embodiment of fig. 8 can be implemented as the input device in the embodiment of fig. 7.

for the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.

The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

as will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

these computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.

finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or terminal apparatus that comprises the element.

The identity verification method, the identity verification device and the storage medium provided by the present application are described in detail above, and specific examples are applied in the present application to explain the principles and implementations of the present application, and the description of the above embodiments is only used to help understand the method and the core ideas of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims

1. An identity verification method, comprising:

acquiring a plurality of identity identifications corresponding to a user to be verified; wherein the plurality of identity identifications comprise unique identity identifications and non-unique identity identifications;

Determining the blacklist as a target blacklist associated with the user to be verified under the condition that any target non-unique blacklist identifier matched with the unique identity identifier does not exist in unique blacklist identifiers of the blacklist and at least one target non-unique blacklist identifier respectively matched with the non-unique identity identifier exists in non-unique blacklist identifiers of the blacklist;

2. The method of claim 1, wherein the determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier comprises:

3. The method of claim 1, wherein the determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier comprises:

Acquiring the associated parameters of each target non-unique blacklist mark;

4. the method of claim 1, further comprising, before the determining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier:

Acquiring the priority of each target non-unique blacklist mark;

5. The method of claim 4, wherein the obtaining the matching degree between the user to be verified and the target blacklist according to the target non-unique blacklist identifier corresponding to the highest priority comprises:

6. the method according to claim 1, wherein, in a case that the target blacklist includes a plurality of blacklists, the performing identity verification on the user to be verified according to the matching degree includes:

acquiring blacklist grade parameters preset by each target blacklist;

7. The method according to claim 1, wherein, in a case that the target blacklist includes a plurality of blacklists, the performing identity verification on the user to be verified according to the matching degree includes:

8. the method according to claim 7, wherein the performing identity verification on the user to be verified through the maximum matching degree comprises:

determining the user to be verified as a blacklist user under the condition that the maximum matching degree is greater than or equal to a second preset threshold value; alternatively, the first and second electrodes may be,

9. An identity verification apparatus, the apparatus comprising:

10. The apparatus of claim 9, wherein the matching degree obtaining module comprises:

11. The apparatus of claim 9, wherein the matching degree obtaining module comprises:

12. The apparatus of claim 9, further comprising:

13. The apparatus of claim 12, wherein the matching degree obtaining module comprises:

14. The apparatus of claim 9, wherein in the case that the target blacklist includes a plurality of blacklists, the identity verification module comprises:

the verification parameter acquisition sub-module is used for acquiring the verification parameters of the user to be verified according to the blacklist grade parameter corresponding to each target blacklist and the matching degree between each target blacklist and the user to be verified;

15. The apparatus of claim 9, wherein in the case that the target blacklist includes a plurality of blacklists, the identity verification module comprises:

16. The apparatus according to claim 15, wherein the second identity verification sub-module is configured to determine that the user to be verified is a blacklisted user if the maximum matching degree is greater than or equal to a second preset threshold; alternatively, the first and second electrodes may be,

17. an identity verification device, comprising a processor and a memory, wherein,

The processor executes the computer program code stored in the memory to perform the steps of the identity verification method of any one of claims 1 to 8.

18. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the identity verification method of any one of claims 1 to 8.