CN113691541B

CN113691541B - Registration verification method and system based on block chain

Info

Publication number: CN113691541B
Application number: CN202110981965.3A
Authority: CN
Inventors: 丁宇轩; 周亚
Original assignee: Nupt Institute Of Big Data Research At Yancheng; Chengdu Zowola Technology Co ltd
Current assignee: Nupt Institute Of Big Data Research At Yancheng; Chengdu Zowola Technology Co ltd
Priority date: 2021-08-25
Filing date: 2021-08-25
Publication date: 2023-03-14
Anticipated expiration: 2041-08-25
Also published as: CN113691541A

Abstract

The invention provides a registration verification method and a system based on a block chain, wherein the method comprises the following steps: step S1: acquiring a plurality of items to be verified, wherein the items to be verified comprise: a registrant and a registration application that the registrant wants to register; step S2: determining an acquisition strategy corresponding to the registered application based on a preset acquisition strategy library; and step S3: acquiring verification information of a registrant from a block chain based on an acquisition strategy; and step S4: and verifying the registrant based on the verification information, and allowing the registrant to register the registration application if the registrant passes the verification. According to the block chain-based registration verification method and system, when a user wants to register an application, historical behavior information and the like of a registrant are obtained from the block chain, the registrant is verified, and only after the verification is passed, the registrant can register, so that the registration threshold is increased, and the possibility of malicious events in the application is reduced.

Description

Registration verification method and system based on block chain

Technical Field

The present invention relates to the field of blockchain technologies, and in particular, to a method and a system for verifying registration based on a blockchain.

Background

At present, when a user registers an application, most users only verify whether the registration information filled by the user is complete and real, and whether the user can register is not judged based on the historical behavior of the user, so that the possibility of malicious events occurring in the application is increased, and therefore a solution is needed urgently.

Disclosure of Invention

One of the objectives of the present invention is to provide a method and a system for verifying registration based on a blockchain, wherein when a user wants to register an application, historical behavior information of a registrant is obtained from the blockchain, and the registrant is verified.

The embodiment of the invention provides a registration verification method based on a block chain, which comprises the following steps:

step S1: acquiring a plurality of items to be verified, wherein the items to be verified comprise: registrars and registration applications that registrars want to register;

step S2: determining an acquisition strategy corresponding to the registered application based on a preset acquisition strategy library;

and step S3: acquiring verification information of a registrant from a block chain based on an acquisition strategy;

and step S4: and verifying the registrant based on the verification information, and allowing the registrant to register the registration application if the registrant passes the verification.

Preferably, step S3: acquiring the verification information of the registrant from the blockchain based on the acquisition strategy, wherein the verification information comprises the following steps:

extracting and acquiring a strategy item in the strategy, wherein the strategy item comprises: a maximum active association level and a maximum passive association level;

determining a plurality of first users actively associated by a registrant and a first active association level of the first users based on a preset active association library;

if the first active association level is less than or equal to the maximum active association level, taking the corresponding first user as a first associated person;

determining a plurality of second users passively associated with the registrant and a first passive association level of the second users based on a preset passive association library;

if the second passive association level is less than or equal to the maximum passive association level, taking the corresponding second user as a second associated person;

acquiring a first historical behavior record of a registrant, a second historical behavior record of a first associated person and a third historical behavior record of a second associated person from a blockchain;

and taking the first historical behavior record, the second historical behavior record and the third historical behavior record as the verification information of the registrant to finish the acquisition.

Preferably, in step S4, the authenticating the registrant based on the authentication information includes:

extracting a plurality of first entries in the authentication information, the first entries including: the first behavior, the first behavior generation time, the first behavior occurrence scene, the behavior person and the additional item, wherein the behavior person comprises: a registrant or a first associate or a second associate;

performing feature extraction on the first behavior to obtain a plurality of first features;

acquiring a preset malicious feature library, matching the first feature with a second feature in the malicious feature library, and determining whether the matching is in accordance;

if so, determining a second characteristic which is matched and matched, and serving as a third characteristic, and simultaneously associating with the corresponding action, and in addition, determining first action generation time corresponding to the first action, serving as second action generation time, determining a first action occurrence scene corresponding to the first action, and serving as a second action occurrence scene;

extracting an acquisition node in the additional item, and acquiring fermentation information through the acquisition node, wherein the fermentation information comprises: a fourth historical behavior record of a plurality of participants other than the registrant in the second behavior occurrence scenario after the second behavior generation time;

extracting a plurality of second entries in the fourth historical behavior record, the second entries comprising: a second action;

determining a capturing mode corresponding to the third feature based on a preset capturing mode library;

capturing a plurality of first suspicious behaviors in the second behaviors based on the capturing mode;

extracting the features of the first suspicious behavior to obtain a plurality of fourth features;

determining a plurality of first fermentation characteristics corresponding to the third characteristics based on a preset fermentation characteristic library;

matching the fourth characteristic with the first fermentation characteristic to determine whether the matching is in accordance;

if yes, determining the matched first fermentation characteristics, taking the matched first fermentation characteristics as second fermentation characteristics, and associating the second fermentation characteristics with the corresponding actor;

when the behavior associated with the third feature is a registrant, determining a first malicious value corresponding to the third feature based on a preset registrant malicious library;

when the behavior associated with the third feature is a first associated person, determining a first active association level of the first associated person, and determining a second malicious value corresponding to the third feature and the second active association level together based on a preset associated person malicious library as a second active association level;

when the behavior associated with the third feature is a second associated person, determining a first passive association level of the second associated person, and determining a third malicious value corresponding to the third feature and the second passive association level together based on the associated person malicious library as a second passive association level;

when the behavior associated with the second fermentation characteristic is a registrant, determining a fourth malicious value corresponding to the second fermentation characteristic based on the registrant malicious library;

when the behavior related to the second fermentation characteristic is a first related person, determining a first active related level of the first related person, and determining a fifth malicious value corresponding to the second fermentation characteristic and the third active related level together based on a related person malicious library as a third active related level;

when the behavior related to the second fermentation characteristic is a second related person, determining a first passive related hierarchy of the second related person as a third passive related hierarchy, and determining a sixth malicious value corresponding to the second fermentation characteristic and the third passive related hierarchy together based on a related person malicious library;

summarizing a first malicious value, a second malicious value, a third malicious value, a fourth malicious value, a fifth malicious value and a sixth malicious value to obtain a malicious value sum;

if the malicious value sum is smaller than the preset malicious value sum threshold, the registrant passes the verification, otherwise, the registrant does not pass the verification.

Preferably, the registration verification method based on the blockchain further includes:

step S5: after the verification is passed, configuring a trigger window, judging whether the registrant triggers the trigger window, and if so, carrying out account cancellation on the registrant;

wherein, configuring the trigger window comprises:

acquiring a preset trigger characteristic library, and dynamically acquiring characteristic items from the trigger characteristic library, wherein the characteristic items comprise: a first single unique and a first combined feature;

when the feature item is the first individual feature, acquiring a preset main sampling frame, and associating the first individual feature with the main sampling frame;

when the feature item is a first combined feature, splitting the first combined feature to obtain a plurality of first split features;

acquiring a plurality of preset sub-sampling frames, and associating the first splitting characteristics with the sub-sampling frames one by one;

determining a combined trigger mode among the first splitting characteristics based on a preset combined trigger mode library;

establishing a combination relation between sub-sampling frames associated with the corresponding first splitting characteristics based on a combination triggering mode;

when the main sampling frame is associated with the first single feature, the sub-sampling frame is associated with the first split feature, and the sub-sampling frame establishes a combined relationship, a preset initial window is obtained, and the main sampling frame and the sub-sampling frame are placed in the initial window;

and when the main sampling frame and the sub-sampling frame are placed successfully, the initial window is used as a trigger window, and the configuration is completed.

Preferably, the determining whether the registered user triggers the trigger window includes:

acquiring a behavior generation point of the registrant in the trigger window;

when the behavior generating point is single, acquiring a first region attribute where the behavior generating point is located;

determining at least one first individual feature corresponding to the first area attribute based on a preset individual feature library, and taking the first individual feature as a second individual feature;

calling a main sampling frame associated with a second individual feature in the trigger window to sample the behavior generation point to obtain a third behavior;

performing feature extraction on the third behavior to obtain a plurality of fifth features;

matching the fifth characteristic with the corresponding second individual characteristic, and if the fifth characteristic is matched with the corresponding second individual characteristic, determining that a user triggers a trigger window;

when the behavior generating points are multiple, acquiring the attribute of a second area where the behavior generating points are located;

determining at least one first splitting feature corresponding to the second region attribute based on a preset first splitting feature library, and taking the first splitting feature as a second splitting feature;

calling a sub-sampling frame associated with a second splitting characteristic in the trigger window to sample the behavior generating point to obtain a fourth behavior;

performing feature extraction on the fourth line to obtain a plurality of sixth features;

combining the corresponding sixth features based on the combination relation between the sub-sampling frames associated with the second split features, and if the combination is successful, obtaining second combined features;

and matching the second combined characteristic with the corresponding first combined characteristic, and determining that the user triggers the trigger window if the second combined characteristic is matched with the corresponding first combined characteristic.

The embodiment of the invention provides a registration verification system based on a block chain, which comprises:

the first obtaining module is used for obtaining a plurality of items to be verified, and the items to be verified comprise: a registrant and a registration application that the registrant wants to register;

the determining module is used for determining an acquisition strategy corresponding to the registered application based on a preset acquisition strategy library;

the second acquisition module is used for acquiring the verification information of the registrant from the block chain based on the acquisition strategy;

and the verification module is used for verifying the registrant based on the verification information, and allowing the registrant to register the registration application if the registrant passes the verification.

Preferably, the second obtaining module performs the following operations:

determining a plurality of first users actively associated with a registrant and a first active association level of the first users based on a preset active association library;

Preferably, the verification module performs the following operations:

if so, determining a second characteristic which is matched and matched, and using the second characteristic as a third characteristic, and simultaneously associating with a corresponding action person, and in addition, determining first action generation time corresponding to the first action, and using the first action generation time as second action generation time, determining a first action occurrence scene corresponding to the first action, and using the first action occurrence scene as a second action occurrence scene;

determining a capture mode corresponding to the third feature based on a preset capture mode library;

if yes, determining the matched first fermentation characteristic, taking the first fermentation characteristic as a second fermentation characteristic, and associating the second fermentation characteristic with the corresponding agent;

when the behavior related to the second fermentation characteristic is the first related person, determining a first active related level of the first related person, taking the first active related level as a third active related level, and determining a fifth malicious value corresponding to the second fermentation characteristic and the third active related level together based on a related person malicious library;

if the malicious value sum is smaller than the preset malicious value sum and the threshold value, the registrant passes the verification, otherwise, the registrant does not pass the verification.

Preferably, the system for registration verification based on blockchain further includes:

the account canceling module is used for configuring a trigger window after the verification is passed, judging whether the registrant triggers the trigger window, and canceling the account of the registrant if the registrant triggers the trigger window;

the sales module performs the following operations:

determining a combined trigger mode among the first split characteristics based on a preset combined trigger mode library;

establishing a combination relation between sub-sampling frames associated with corresponding first splitting characteristics based on a combination triggering mode;

when the main sampling frame is associated with the first single feature, the sub-sampling frames are associated with the first split feature, and the sub-sampling frames are combined, acquiring a preset initial window, and placing the main sampling frame and the sub-sampling frames in the initial window;

Preferably, the sales module performs the following operations:

acquiring a behavior generation point of the registrant in the trigger window;

when a plurality of behavior generating points are arranged, acquiring the attribute of a second area where the behavior generating points are located;

determining at least one first splitting characteristic corresponding to the second region attribute based on a preset first splitting characteristic library, and taking the first splitting characteristic as a second splitting characteristic;

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

fig. 1 is a flowchart of a block chain-based registration verification method according to an embodiment of the present invention;

fig. 2 is a schematic diagram of a block chain-based registration verification system according to an embodiment of the present invention.

Detailed Description

The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it should be understood that they are presented herein only to illustrate and explain the present invention and not to limit the present invention.

The embodiment of the invention provides a registration verification method based on a block chain, as shown in fig. 1, comprising the following steps:

step S1: acquiring a plurality of items to be verified, wherein the items to be verified comprise: a registrant and a registration application that the registrant wants to register;

The working principle and the beneficial effects of the technical scheme are as follows:

the preset acquisition strategy library specifically comprises the following steps: a database, in which the acquisition strategy corresponding to each registered application is stored;

when a registrant wants to register an application, determining an acquisition strategy corresponding to the application, acquiring verification information of the registrant [ historical behavior information of the registrant, historical behavior information of other users associated with the registrant, and the like ] based on the acquisition strategy, and verifying whether the registrant can register the application based on the verification information;

according to the embodiment of the invention, when a user wants to register an application, the historical behavior information of the registrant is acquired from the block chain, the registrant is verified, and only after the verification is passed, the registrant can register, so that the registration threshold is increased, and the possibility of malicious events in the application is reduced.

The embodiment of the invention provides a registration verification method based on a block chain, which comprises the following steps of S3: acquiring the verification information of the registrant from the blockchain based on an acquisition strategy, wherein the acquisition strategy comprises the following steps:

the preset active association library specifically comprises the following steps: a database, in which active association levels of a plurality of active associated users and active associated users that are actively associated with different users [ actively setting a user as an associated user ] are stored [ for example: b is set as an active associated user of the user, B is set as 1 relative to the active associated level of A, C is set as the active associated user of the user, C is set as 2 relative to the active associated level of A, and the like; the preset passive association library specifically comprises the following steps: a database storing a plurality of passive associated users and passive association levels of passive associated users with different user passive associations [ others set themselves as their associated users ] [ for example: a is set as a related user by B, A is a passive related user of B, the passive related level of B relative to A is 1, B is set as a related user by C, B is a passive related user of C, and the passive related level of C relative to A is 2);

the embodiment of the invention adopts an association system, each user needs to actively set a user to be associated with the user before registering, and the association relation can be established only by obtaining the consent of the other party during association; each application sets a maximum active association level and a maximum passive association level according to the self requirement, and the larger the maximum active association level and the maximum passive association level are, the higher the registration threshold is, and the better the effect is.

The embodiment of the invention provides a registration verification method based on a block chain, in step S4, based on verification information, a registrant is verified, and the method comprises the following steps:

extracting features of the first behavior to obtain a plurality of first features;

acquiring a preset malicious feature library, matching the first features with second features in the malicious feature library, and determining whether the matching is met;

extracting the acquisition node in the additional item, and acquiring fermentation information through the acquisition node, wherein the fermentation information comprises: a fourth historical behavior record of a plurality of participants other than the registrant in the second behavior occurrence scenario after the second behavior generation time;

performing feature extraction on the first suspicious behaviors to obtain a plurality of fourth features;

when the behavior related to the third feature is a second related person, determining a first passive related hierarchy of the second related person, and determining a third malicious value corresponding to the third feature and the second passive related hierarchy together based on a related person malicious library as a second passive related hierarchy;

summarizing the first malicious value, the second malicious value, the third malicious value, the fourth malicious value, the fifth malicious value and the sixth malicious value to obtain a malicious value sum;

the preset malicious feature library specifically comprises the following steps: a database, in which a large number of malicious features are stored; the preset capture mode library specifically comprises the following steps: a database, in which capturing modes corresponding to different features are stored [ for example: if the user has the characteristics of uploading the illegal file, the capturing mode is to capture the behaviors of other users opening the illegal file and forwarding the illegal file; the preset fermentation characteristic library specifically comprises the following steps: a database, in which fermentation characteristics corresponding to different characteristics are stored; the preset malicious database of the registrant is specifically as follows: the database stores malicious values corresponding to different characteristics, and the malicious value is larger, so that the malicious degree is higher; the preset associated person malicious library specifically comprises the following steps: the database stores malicious values corresponding to different characteristics and different association levels; the preset malicious value and the threshold are specifically as follows: for example, 20;

according to the embodiment of the invention, based on the association system, the user generates the malicious behaviors, and other users associated with the user are also influenced, so that the cost of the user for generating the malicious behaviors is increased, and the possibility of the user for generating the malicious behaviors is reduced to a certain extent; meanwhile, when malicious behaviors occur, a plurality of fermentation events are generated, the capturing mode is quickly determined based on the capturing mode library, the fermentation events corresponding to the malicious features are captured, and the working efficiency of the system is improved; setting a plurality of malicious libraries, quickly determining malicious values corresponding to different characteristics, and assisting in judging the malicious degree of the behaviors of the user and the associated user; in addition, the active correlation and the passive correlation have different subjectively, the malicious degree is determined separately, and the setting is more reasonable.

The embodiment of the invention provides a registration verification method based on a block chain, which further comprises the following steps:

wherein, configuring the trigger window comprises:

acquiring a preset trigger characteristic library, and dynamically acquiring characteristic items from the trigger characteristic library, wherein the characteristic items comprise: a first single unique and first combined feature;

the preset trigger feature library specifically comprises: a database having a plurality of trigger signatures stored therein, the trigger signatures comprising individual signatures [ for example: publish bad vocabulary information) and combination features [ e.g.: downloading a prepared illegal file on a login cloud disk, and applying for adding a large number of chat groups; the preset main sampling frame specifically comprises the following steps: a sampling frame; the preset multiple sub-sampling frames specifically include: a plurality of sampling frames; the preset combined trigger mode library specifically comprises: a database, in which combination triggering relationships between combination features [ for example: distributing the downloaded illegal files in a large number of added chat groups; the preset initial window specifically comprises the following steps: a system window; the dynamic acquisition specifically comprises: continuously obtaining;

and when a feature item is obtained from the trigger feature library, configuring the corresponding main sampling frame and the corresponding sub sampling frame to be placed in the initial window, and after the main sampling frame and the sub sampling frame are completely placed, completing the configuration of the trigger window.

The embodiment of the invention provides a registration verification method based on a block chain, which is used for judging whether a registered user triggers a trigger window or not, and comprises the following steps:

acquiring a behavior generation point of the registrant in the trigger window;

extracting features of the third behavior to obtain a plurality of fifth features;

the preset individual feature library specifically comprises: a database having different region attributes [ e.g.: download button area, etc. ] corresponding features that may produce malicious behavior [ individual features ]; the preset first splitting characteristic library specifically comprises the following steps: a database, in which features (splitting features) which are corresponding to different region attributes and are likely to generate malicious behaviors are stored;

determine that the user is within a preset time period [ e.g.: when the behavior generating points are single, calling a corresponding main sampling frame to sample a third behavior, performing feature extraction on the third behavior to obtain a fifth feature, matching the fifth feature with a corresponding second individual feature, and if the matching is successful, independently generating malicious behaviors by a user, and triggering a trigger window; when the behavior generation points are multiple, calling the sub-sampling frame to respectively adopt a fourth behavior, carrying out feature extraction on the fourth behavior to obtain a sixth feature, combining the sixth feature based on the corresponding combination relation to obtain a second combination feature, matching the second combination feature with the corresponding first combination feature, and if the second combination feature is matched with the corresponding first combination feature, generating a malicious behavior by the user combination and triggering a trigger window;

in actual use, there may be a special case that: the user and the associated user of the user know the verification mechanism and keep good behavior records, then a new application is registered at the same time, and the time is determined to be good, and malicious events are generated together, so that the verification can be passed and the malicious events can be generated, and when the system administrator monitors the events, the events are late, therefore, after the user is successfully registered, a trigger window is configured, whether the user generates single malicious events and combined malicious events is detected, the occurrence of the characteristic condition can be effectively avoided, the system is more comprehensive, the response capability of the system is improved, and the good order and the use environment in the application can be ensured.

An embodiment of the present invention provides a block chain-based registration verification system, as shown in fig. 2, including:

a first obtaining module 1, configured to obtain a plurality of items to be verified, where the items to be verified include: registrars and registration applications that registrars want to register;

the determining module 2 is used for determining an obtaining strategy corresponding to the registered application based on a preset obtaining strategy library;

the second acquisition module 3 is used for acquiring the verification information of the registrant from the block chain based on the acquisition strategy;

and the verification module 4 is used for verifying the registrant based on the verification information, and allowing the registrant to register the registration application if the registrant passes the verification.

according to the embodiment of the invention, when a user wants to register a certain application, the historical behavior information of the registrant is acquired from the block chain, the registrant is verified, and only after the verification is passed, the registrant can register, so that the registration threshold is increased, and the possibility of malicious events in the application is reduced.

The embodiment of the invention provides a registration verification system based on a block chain, wherein a second acquisition module 3 executes the following operations:

the preset active association library specifically comprises the following steps: a database, which stores a plurality of active associated users and active associated levels of active associated users, where different users are actively associated [ actively setting a user as an associated user of the user ] [ for example: b is set as the active associated user of the user A, B is 1 relative to the active associated level of the user A, C is set as the active associated user of the user B, C is 2 relative to the active associated level of the user A, and the like; the preset passive association library specifically comprises the following steps: a database storing a plurality of passive associated users and passive association levels of passive associated users with different user passive associations [ others set themselves as their associated users ] [ for example: a is set as a related user by B, A is a passive related user of B, the passive related level of B relative to A is 1, B is set as a related user by C, B is a passive related user of C, and the passive related level of C relative to A is 2);

The embodiment of the invention provides a registration verification system based on a block chain, wherein a verification module 4 executes the following operations:

the preset malicious feature library specifically comprises the following steps: a database in which a plurality of malicious features are stored; the preset capture mode library specifically comprises the following steps: a database, in which capturing modes corresponding to different features are stored [ for example: if the user has the characteristics of uploading the illegal file, the capturing mode is to capture the behaviors of other users opening the illegal file and forwarding the illegal file; the preset fermentation characteristic library specifically comprises the following steps: a database, in which fermentation characteristics corresponding to different characteristics are stored; the preset malicious database of the registrant is specifically as follows: the database stores malicious values corresponding to different characteristics, and the malicious value is larger, so that the malicious degree is higher; the preset associated person malicious library specifically comprises the following steps: the database stores malicious values corresponding to different characteristics and different association levels; the preset malicious value and the threshold are specifically as follows: for example, 20;

according to the embodiment of the invention, based on the association system, the user generates the malicious behaviors, and other users associated with the user are also influenced, so that the cost of the user for generating the malicious behaviors is increased, and the possibility of the user for generating the malicious behaviors is reduced to a certain extent; meanwhile, when malicious behaviors occur, a plurality of fermentation events are generated, the capturing mode is determined quickly based on the capturing mode library, the fermentation events corresponding to the malicious characteristics are captured, and the working efficiency of the system is improved; setting a plurality of malicious libraries, quickly determining malicious values corresponding to different characteristics, and assisting in judging the behavior malicious degree of the user and the associated user; in addition, the active correlation and the passive correlation have different subjectivity, and the malicious degree is determined separately, so that the setting is more reasonable.

The embodiment of the invention provides a registration verification system based on a block chain, which further comprises:

the account cancellation module is used for configuring a trigger window after the verification is passed, judging whether the registrant triggers the trigger window, and canceling the account of the registrant if the registrant triggers the trigger window;

the sales module performs the following operations:

the preset trigger feature library specifically comprises: a database having a plurality of trigger signatures stored therein, the trigger signatures comprising individual signatures [ for example: publish bad vocabulary information) and combination features [ e.g.: downloading a prepared illegal file in a login cloud disk, and applying for adding a large number of chat groups; the preset main sampling frame specifically comprises the following steps: a sampling frame; the preset multiple sub-sampling frames specifically include: a plurality of sampling frames; the preset combined trigger mode library specifically comprises: a database, in which combination triggering relationships between combination features [ for example: distributing the downloaded illegal files in a large number of added chat groups; the preset initial window specifically comprises the following steps: a system window; the dynamic acquisition specifically comprises: continuously obtaining;

The embodiment of the invention provides a registration verification system based on a block chain, wherein an account cancellation module executes the following operations:

acquiring a behavior generation point of the registrant in the trigger window;

combining the corresponding sixth features based on the combination relation between the sub-sampling frames associated with the second split feature, and if the combination is successful, obtaining a second combined feature;

determine that the user is within a preset time period [ e.g.: 10 seconds) generating a plurality of behavior generating points (determined by tracking the clicking operation of the user), calling a corresponding main sampling frame to sample a third behavior when the behavior generating points are single, extracting the characteristics of the third behavior to obtain a fifth characteristic, matching the fifth characteristic with a corresponding second individual characteristic, and if the matching is successful, independently generating malicious behaviors by the user and triggering a trigger window; when the behavior generation points are multiple, calling the sub-sampling frame to respectively adopt a fourth behavior, carrying out feature extraction on the fourth behavior to obtain a sixth feature, combining the sixth feature based on the corresponding combination relation to obtain a second combination feature, matching the second combination feature with the corresponding first combination feature, and if the second combination feature is matched with the corresponding first combination feature, generating a malicious behavior by the user combination and triggering a trigger window;

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims

1. A registration verification method based on a block chain is characterized by comprising the following steps:

step S1: obtaining a plurality of items to be verified, wherein the items to be verified comprise: a registrant and a registration application that the registrant wants to register;

and step S3: acquiring the verification information of the registrant from the blockchain based on the acquisition strategy;

and step S4: verifying the registrant based on the verification information, and allowing the registrant to register the registration application if the registrant passes the verification;

the step S3: acquiring the verification information of the registrant from the blockchain based on the acquisition strategy, wherein the verification information comprises the following steps:

extracting a strategy item in the acquisition strategy, wherein the strategy item comprises: a maximum active association level and a maximum passive association level;

determining a plurality of first users actively associated with the registrant and a first active association level of the first users based on a preset active association library;

if the first passive association level is less than or equal to the maximum passive association level, taking the corresponding second user as a second associated person;

acquiring a first historical behavior record of the registrant, a second historical behavior record of the first associated person and a third historical behavior record of the second associated person from a block chain;

2. The blockchain-based enrollment authentication method of claim 1, wherein the step S4 of authenticating the enrollee based on the authentication information includes:

extracting a plurality of first entries in the authentication information, the first entries including: a first action, a first action generation time, a first action occurrence scenario, an action person, and additional items, the action person comprising: the registrant or the first associate or the second associate;

acquiring a preset malicious feature library, matching the first features with second features in the malicious feature library, and determining whether the first features and the second features are matched;

if so, determining the second characteristic which is matched and matched, and serving as a third characteristic, and simultaneously associating with the corresponding action, otherwise, determining the first action generation time corresponding to the first action, serving as a second action generation time, determining the first action occurrence scene corresponding to the first action, and serving as a second action occurrence scene;

extracting an acquisition node in the additional item, and acquiring fermentation information through the acquisition node, wherein the fermentation information comprises: a fourth historical record of behavior of a plurality of participants in the second behavior occurrence scenario other than the enrollee after the second behavior generation time;

performing feature extraction on the first suspicious behavior to obtain a plurality of fourth features;

if yes, determining the first fermentation characteristics which are matched and matched, taking the first fermentation characteristics as second fermentation characteristics, and meanwhile, associating the first fermentation characteristics with the corresponding agents;

when the behavior associated with the third feature is the registrant, determining a first malicious value corresponding to the third feature based on a preset registrant malicious library;

when the behavior related to the third feature is the first related person, determining the first active related hierarchy of the first related person, and determining a second malicious value corresponding to the third feature and the second active related hierarchy together based on a preset related person malicious library as a second active related hierarchy;

when the behavior person associated with the third feature is the second associated person, determining the first passive association level of the second associated person, and determining a third malicious value corresponding to the third feature and the second passive association level together based on the associated person malicious library as a second passive association level;

when the behavior associated with the second fermentation characteristic is the registrant, determining a fourth malicious value corresponding to the second fermentation characteristic based on the registrant malicious library;

when the behavior associated with the second fermentation characteristic is the first associated person, determining the first active association level of the first associated person, and determining a fifth malicious value jointly corresponding to the second fermentation characteristic and the third active association level based on the associated person malicious library as a third active association level;

when the behavior related to the second fermentation characteristic is the second related person, determining the first passive related hierarchy of the second related person, and determining a sixth malicious value jointly corresponding to the second fermentation characteristic and the third passive related hierarchy based on the related person malicious library as a third passive related hierarchy;

and if the malicious value sum is smaller than a preset malicious value sum threshold, the registrant passes the verification, otherwise, the registrant does not pass the verification.

3. The blockchain-based registration verification method of claim 2, further comprising:

wherein, configuring the trigger window comprises:

acquiring a preset trigger feature library, and dynamically acquiring feature items from the trigger feature library, wherein the feature items comprise: a first single unique and a first combined feature;

when the feature item is the first combined feature, splitting the first combined feature to obtain a plurality of first split features;

establishing a combination relation between the sub-sampling frames corresponding to the first split feature association based on the combination triggering mode;

when the main sampling frame is associated with the first individual feature, the sub-sampling frame is associated with the first split feature, and the combination relationship between the sub-sampling frame and the corresponding first split feature is established, acquiring a preset initial window, and placing the main sampling frame and the sub-sampling frame in the initial window;

4. The blockchain-based enrollment verification method of claim 3, wherein determining whether the enrollee triggered the trigger window comprises:

acquiring a behavior generation point of the registrant in the trigger window;

calling the main sampling frame associated with the second individual feature in the trigger window to sample the behavior generating point to obtain a third behavior;

matching the fifth feature with the corresponding second individual feature, and if the fifth feature is matched with the corresponding second individual feature, determining that the user triggers the trigger window;

when the number of the behavior generating points is multiple, acquiring the attribute of a second area where the behavior generating points are located;

determining at least one first splitting feature corresponding to the second region attribute based on a preset first splitting feature library, and using the first splitting feature as a second splitting feature;

calling the sub-sampling frame associated with the second splitting feature in the trigger window to sample the behavior generating point to obtain a fourth behavior;

combining the corresponding sixth features based on the combination relationship between the sub-sampling frames associated with the second split feature, and if the combination is successful, obtaining a second combined feature;

and matching the second combined feature with the corresponding first combined feature, and determining that the user triggers the trigger window if the second combined feature is matched with the corresponding first combined feature.

5. A blockchain-based enrollment verification system, comprising:

a first obtaining module, configured to obtain a plurality of items to be verified, where the items to be verified include: a registrant and a registration application that the registrant wants to register;

the verification module is used for verifying the registrant based on the verification information, and if the registrant passes the verification, the registrant is allowed to register the registration application;

the second obtaining module performs the following operations:

acquiring a first historical behavior record of the registrant, a second historical behavior record of the first associated person and a third historical behavior record of the second associated person from a blockchain;

6. The blockchain-based enrollment authentication system of claim 5, wherein the authentication module performs the following operations:

if so, determining the second characteristic which is matched and matched, and using the second characteristic as a third characteristic, and simultaneously associating the second characteristic with the corresponding action person, and in addition, determining the first action generation time corresponding to the first action, and using the first action generation time as a second action generation time, and determining the first action occurrence scene corresponding to the first action, and using the first action occurrence scene as a second action occurrence scene;

capturing a plurality of first suspicious behaviors in the second behaviors based on the capturing manner;

if yes, determining the first fermentation characteristics matched with the first fermentation characteristics, using the first fermentation characteristics as second fermentation characteristics, and associating the first fermentation characteristics with the corresponding agent;

when the behavior associated with the third feature is the first associated person, determining the first active association level of the first associated person, and determining a second malicious value corresponding to the third feature and the second active association level together based on a preset associated person malicious library as a second active association level;

when the behavior associated with the third feature is the second associated person, determining the first passive association level of the second associated person, and determining a third malicious value corresponding to the third feature and the second passive association level together based on the associated person malicious library as a second passive association level;

when the behavior associated with the second fermentation characteristic is the first associated person, determining the first active association level of the first associated person as a third active association level, and determining a fifth malicious value corresponding to the second fermentation characteristic and the third active association level together based on the associated person malicious library;

if the malicious value sum is smaller than a preset malicious value sum threshold value, the registrant passes the verification, otherwise, the registrant does not pass the verification.

7. The blockchain-based enrollment verification system of claim 6, further comprising:

the account cancellation module is used for configuring a trigger window after the verification is passed, judging whether the registrant triggers the trigger window, and if so, canceling the account of the registrant;

the subscriber module performs the following operations:

determining a combined trigger mode among the first split features based on a preset combined trigger mode library;

8. The blockchain-based enrollment verification system of claim 7, wherein the subscriber module performs the following operations:

acquiring a behavior generation point of the registrant in the trigger window;

and matching the second combined feature with the corresponding first combined feature, and if the second combined feature is matched with the corresponding first combined feature, determining that the user triggers the trigger window.