CN118096191A - Anti-fraud system and method for intelligent user information protection - Google Patents
Anti-fraud system and method for intelligent user information protection Download PDFInfo
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Abstract
The invention relates to the technical field of user information protection management, and discloses an intelligent user information protection anti-fraud system and method, wherein the system comprises an anti-fraud user side communication platform management module, an anti-fraud user side incoming call contact management module and an anti-fraud warning management module; the facial feature image parameters of strangers or historic familiarity are acquired and backed up through the mobile terminal shooting lens, so that the safety of a user information protection anti-fraud system is improved; based on an intelligent search algorithm, the communication text characteristic parameters of the user and the incoming contact person are matched with scientifically preset user-side communication property text keyword parameters to realize intelligent identification of property fraud risk events in the communication process of the user and the incoming contact person, realize autonomous online feedback warning of the user and the incoming contact person, and reduce the risk of fraud caused by information leakage of the user.
Description
Technical Field
The invention relates to the technical field of user information protection management, in particular to an intelligent user information protection anti-fraud system and method.
Background
The user information protection is to protect personal information such as citizen identity, property and the like. With the popularity of internet applications and the reliance of people on the internet, personal information is greatly compromised. Malicious programs, various phishing and fraud continue to be increased at a high speed, and meanwhile, hacking and large-scale personal information leakage events are frequent, so that the leakage and property loss of a large amount of netizens personal information are increased along with the great increase of various network attacks. The user privacy information is revealed, personal property is lost, and the revealed personal information comprises basic information, equipment information, account information, privacy information, social relationship information, network behavior information and the like. Human resale information, mobile phone leakage, PC computer infection and website loopholes are four major ways of personal information leakage. The user information leakage types are as follows: 1. basic information. To accomplish most of the network activities, consumers submit personal basic information including name, gender, age, identification card number, phone number, email address, home address, etc. according to the requirements of the service provider, and sometimes even personal basic information including marital, belief, occupation, work units, income, etc. with relative privacy. 2. Device information. The system mainly refers to basic information of various computer terminal devices (including mobile and fixed terminals) used by consumers, such as location information, wifi list information, mac address, CPU information, memory information, SD card information, operating system version and the like. 3. Account information. The method mainly comprises an online banking account, a third party payment account, a social account, an important mailbox account and the like. 4. Privacy information. The system mainly comprises address book information, call records, short message records, IM application software chat records, personal videos, photos and the like. 5. Social relationship information. This mainly includes friend relationship, family member information, work unit information, and the like. 6. Network behavior information. The system mainly refers to internet surfing behavior records, various activities of consumers on the network, such as internet surfing time, internet surfing places, input records, chat friends, website access behaviors, network game behaviors and other personal information. Meanwhile, lawless persons can not carry out intelligent recognition of crowd relation types on incoming contact persons of users, can not carry out identity information acquisition backup on strangers and historical familiarity, can not accurately recognize property communication information between strangers and historical familiarity and users, and can not timely give users anti-fraud warning.
The Chinese patent application with publication number of CN108038701A discloses an integrated learning anti-fraud test method, which adopts a training sample set to extract characteristics of user information in the training sample set; training a base classifier, and training the feature view by adopting a plurality of classification algorithms to obtain a base classifier set; processing the base classifier set by using an ensemble learning method to obtain an ensemble classification model; and classifying the test sample by using the integrated classification model to obtain a test result, and integrating by using another machine learning algorithm to obtain a final result. The embodiment of the invention also discloses an integrated learning anti-fraud test system based on the method. The invention effectively tests the fraudulent user object in the internet transaction, and has better generalization and higher stability. However, the above technical solution cannot intelligently identify the customer relationship type between the user and the financial institution, and cannot perform identity information acquisition backup on the potentially fraudulent user.
Disclosure of Invention
(One) solving the technical problems
The system solves the problems that the existing anti-fraud system cannot intelligently identify the crowd relationship types of incoming contact persons of users, can not collect and backup identity information of strangers and historical familiarity, can not accurately identify property communication information between strangers and historical familiarity and users, and can not give anti-fraud warning to users in time, and achieves the purposes of online identification of the communication platform types of the users, intelligent judgment of the crowd relationship types between the users and the incoming contact persons, identification of the identity information collection backup of strangers and the historical familiarity, accurate identification of chat property fraud events between strangers and the historical familiarity and users and intelligent anti-fraud warning.
(II) technical scheme
The invention is realized by the following technical scheme: an anti-fraud method for intelligent user information protection, the method comprising the steps of:
S1, acquiring characteristic image data of a communication platform of a user side;
S2, matching the image characteristics of the user side communication platform with the image characteristics of the user side communication platform type by adopting a data identification algorithm, analyzing the user side communication platform type data according to the image characteristics matching result of the user side communication platform and outputting the data;
S3, searching out a user side communication platform according to the type data of the user side communication platform by adopting a data searching algorithm and storing contact person contact data in the corresponding user side communication platform; collecting contact data of incoming call contacts of a user communication platform;
S4, matching the contact person contact data of the user side communication platform with the contact person contact data stored in the user side communication platform by adopting a data search algorithm, and generating primary judgment result data of the relationship type between the user and the incoming contact person group according to the contact person contact data matching result of the user side communication platform;
S5, when the primary judgment result data of the relationship type of the user and the incoming contact person group is a to-be-determined familiarity, collecting the last historical communication time point data of the user and the incoming contact person, and the current communication time point data of the user and the incoming contact person; measuring the communication interval time period data of the user and the incoming call contact according to the last historical communication time point data of the user and the incoming call contact and the current communication time point data of the user and the incoming call contact; the data search algorithm is adopted to compare the communication interval time period data of the user and the incoming call contact person with the communication interval time period data of the reasonable communication interval time period data of the user and the incoming call contact person, and secondary judgment result data of the relationship type between the user and the incoming call contact person group is generated according to the comparison result of the communication interval time period data of the user and the incoming call contact person;
S6, collecting facial feature image data of the incoming contact person when the primary judgment result data of the relationship type between the user and the incoming contact person is a stranger or the secondary judgment result data of the relationship type between the user and the incoming contact person is a historical familiar person, and communicating text feature data between the user and the incoming contact person;
and S7, matching the communication text characteristic data of the user and the incoming contact with the communication text keyword data of the user terminal by adopting a data search algorithm, generating communication fraud risk identification data of the user and the incoming contact according to a matching result of the communication text keyword of the user and the incoming contact, and executing anti-fraud feedback warning operation according to the communication fraud risk identification data of the user and the incoming contact.
Preferably, the operation steps for collecting the characteristic image data of the user side communication platform are as follows:
characteristic image data of a user side communication platform use interface is collected online through screen capturing software and characteristic image data of the user side communication platform are generated The screen capturing software comprises FastStoneCapture, a screen recording screenshot eidolon and ShareX, lightshot, and the client communication platform comprises any one of QQ, weChat, MOMO, easily trusted and mobile phone call.
Preferably, the step of matching the image features of the user side communication platform by using the data recognition algorithm to the image features of the user side communication platform and the image features of the user side communication platform type features, and analyzing and outputting the image features of the user side communication platform type data according to the image features matching result of the user side communication platform is as follows:
s21, establishing a user communication platform type characteristic image data set ,; Wherein/>Represents the/>Type characteristic image data of user side communication platform corresponding to user side communication platformA maximum value representing the number of types of the communication platform at the user side;
S22, adopting a data recognition algorithm to carry out characteristic image data of the user side communication platform Communication platform type characteristic image data set/>, with the user sideType characteristic image data/>, of medium user terminal communication platformImage feature matching of the user side communication platform is carried out, and the specific operation steps of executing the image feature matching of the user side communication platform by the data identification algorithm are as follows:
s221, initializing parameters, and updating the maximum iteration times T of an algorithm;
s222, initializing the position of the sea-gull population, namely updating the type characteristic image data set of the communication platform in the user by the sea-gull population Searching for a location in the space;
s223, calculating a fitness value and reserving a global optimal position;
s224, migration and global search: the migratory behavior of the seagulls mainly comprises three steps, namely, collision avoidance conditions are required to be met, and population diversity is ensured; a second direction in which the optimal position is to be calculated; thirdly, moving to a new position according to the direction of the optimal position;
s2241, calculating type characteristic image data set of communication platform of seagull at user side New position/>, without collision with adjacent seagulls during motion in search space;
,/>Wherein/>Communication platform type characteristic image data set/>, at user terminal, for seagullSearching for a current location in the space; /(I)The current iteration number; /(I)Communication platform type characteristic image data set/>, at user terminal, for seagullMotion behavior in the search space; /(I)To control/>A function of the variation frequency;
s2242, calculate the direction of the best position ;/>,Wherein/>Representing feature image data/>, of communication platform with user sideMost matched user side communication platform type characteristic image data/>Communication platform type characteristic image data set/>, at userCurrent best position in search space,/>Communication platform type characteristic image data set/>, at user terminal, for seagullSearching for a current location in the space; /(I)Random numbers to balance global and local search capabilities; /(I)A random number in a value [0,1] interval;
S2243, move to new position according to direction of the best position ,
I.e. according to the direction of the optimal position, the type characteristic image data set/>, of the communication platform at the user sideSearching type characteristic image data/>, of a user side communication platform, in the search spaceIs a new location of (2);
S225, attacking the prey, searching locally, and performing spiral movement in the air when the seagull attacks the prey, wherein the new position is after the seagull attacks the prey ,/>I.e. seagull at user terminal communication platform type characteristic image data set/>The characteristic image data/>, of the communication platform at the user side, is displayed in the search spaceCommunication platform type characteristic image data/>, with user sideImage feature matching of the user side communication platform is carried out, and image data/>, which is characteristic of the user side communication platform, is searched outMatched user side communication platform type characteristic image data/>Corresponding prey;
s226, when the maximum iteration times are met, outputting the characteristic image data of the communication platform of the user side Matched user side communication platform type characteristic image data/>Image matching results of (a); otherwise, returning to the step S223;
S23, outputting all user side communication platform characteristic image data according to the step S226 Matched user side communication platform type characteristic image data/>Generating user side communication platform type data/>And output.
Preferably, the data searching algorithm searches out a user side communication platform according to the type data of the user side communication platform and stores contact person contact data in the corresponding user side communication platform; the operation steps for collecting the contact data of the incoming call contact person of the user communication platform are as follows:
S31, adopting a breadth-first search algorithm to obtain the type data of the user side communication platform Searching contact person contact data stored in a user side communication platform in a corresponding user side communication platform, generating a contact person contact data set/>, stored in the user side communication platform, and storing the contact person contact data set/>,/>; Wherein/>Represents the/>The personal user communication platform stores contact person contact data,/>The method comprises the steps of representing the maximum value of the number of the saved contacts of a user side communication platform, wherein the saved contact data of the user side communication platform comprises a communication platform account number and a communication platform name of the saved contacts;
S32, collecting contact data of incoming contact persons of the user side communication platform through the user side communication platform and generating contact data of the incoming contact persons of the user side communication platform The incoming contact data of the user side communication platform comprise a communication platform account number and a communication platform name of the incoming contact.
Preferably, the step of matching the contact person contact data of the user side communication platform with the contact person contact data stored in the user side communication platform by using a data search algorithm and generating one-time judgment result data of the relationship type between the user and the incoming contact person group according to the contact person contact data matching result of the user side communication platform is as follows:
adopting a unified cost search algorithm to enable incoming call contact person contact data of the user communication platform Storing contact person contact data set/>, with the user side communication platformThe medium-user communication platform stores contact person contact data/>Matching contact person contact data of the user side communication platform, and generating one-time judging result data/>, of the relationship type of the user and the incoming contact person group, according to the contact person contact data matching result of the user side communication platform;
When (when)And/>Successfully matching contact data of contacts of the user side communication platform, indicating that the incoming contact belongs to the contacts stored by the user side communication platform, and outputting one-time judging result data/>, of the relationship types of the user and the incoming contact groupIs a pending familiar person;
When (when) And/>The contact person contact data of the user side communication platform is successfully matched, the fact that the incoming contact person does not belong to the contact person stored in the user side communication platform is indicated, and one-time judging result data/>, of the relationship type between the user and the incoming contact person group, is outputIs a stranger.
Preferably, when the primary judgment result data of the relationship type between the user and the incoming contact person group is a to-be-determined familiarity, collecting the last historical communication time point data of the user and the incoming contact person, and the current communication time point data of the user and the incoming contact person; measuring the communication interval time period data of the user and the incoming call contact according to the last historical communication time point data of the user and the incoming call contact and the current communication time point data of the user and the incoming call contact; and adopting a data search algorithm to compare the communication interval time period data of the user and the incoming call contact with the communication interval time period data of the reasonable user and the incoming call contact, and generating secondary judgment result data of the relationship type between the user and the incoming call contact group according to the comparison result of the communication interval time period data of the user and the incoming call contact, wherein the operation steps are as follows:
S51, the user and the incoming contact person group relationship type one-time judgment result data When the user is a to-be-determined person, acquiring a time point of last historical communication between the user and the incoming contact person through a user side communication platform and generating data/>, of the time point of last historical communication between the user and the incoming contact personWherein/>The unit consists of year, month, day and time;
collecting the current communication time point of the user and the incoming contact person through a user side communication platform and generating the current communication time point data of the user and the incoming contact person Wherein/>The unit consists of year, month, day and time;
s52, according to the last historical communication time point data of the user and the incoming contact And the current communication time point data/>, of the user and the incoming contact personMeasuring data/>, of communication interval time period between user and incoming contact person, by combining time difference measurement formulaWherein/>The unit is h;
S53, establishing reasonable interval time period data for communication between user and incoming contact The data of the reasonable interval time period of the communication between the user and the incoming contact represent the minimum value of the normal communication time length of the relationship between the user and the incoming contact belonging to the familiar crowd;
s54, adopting a unified cost search algorithm to communicate interval time period data between the user and the incoming contact Reasonable interval time period data/>, communicated with user and incoming contactPerforming communication interval time period numerical comparison of the user and the incoming call contact person, and generating secondary judging result data/>, of the relationship type of the user and the incoming call contact person group, according to the communication interval time period numerical comparison result of the user and the incoming call contact person;
When (when)≥/>If the communication time length of the user and the incoming contact person is not less than the minimum value of the normal communication time length belonging to the familiar crowd relationship, outputting one-time judging result data/>, of the relationship type of the user and the incoming contact person groupThe user information anti-fraud detection operation is finished for normal familiarity;
When (when) </>If the communication time length of the user and the incoming contact person is smaller than the minimum value of the normal communication time length belonging to the familiar crowd relationship, outputting one-time judging result data/>, of the relationship type of the user and the incoming contact person groupIs a historic familiar person.
Preferably, when the primary judgment result data of the relationship type between the user and the incoming contact person group is a stranger or the secondary judgment result data of the relationship type between the user and the incoming contact person group is a historical familiarity, facial feature image data of the incoming contact person are collected, and the operation steps of the text feature data of the communication between the user and the incoming contact person are as follows:
When the relationship type of the user and the incoming contact person group is judged at one time, the result data is obtained One-time judging result data/>, for strangers or relationship types of the user and incoming contact groupWhen the mobile terminal shooting lens is a historical familiarity, the mobile terminal shooting lens is used for collecting facial feature images of the incoming contact person and generating facial feature image data/>;
Collecting text data of communication voice between a user and an incoming contact person through a user side communication platform and generating text characteristic data of communication between the user and the incoming contact person。
Preferably, the data search algorithm is adopted to match the text feature data of the communication between the user and the incoming contact with the text keyword data of the communication property at the user end to match the text property keyword of the communication between the user and the incoming contact, the fraud risk identification data of the communication between the user and the incoming contact is generated according to the matching result of the text property keyword of the communication between the user and the incoming contact, and the anti-fraud feedback warning operation is executed according to the fraud risk identification data of the communication between the user and the incoming contact, wherein the operation steps are as follows:
S71, establishing a user communication property text keyword data set ,; Wherein/>Represents the/>Personal user side communication property text keyword data,/>Representing a maximum value of the number of the user-side communication property text keyword data, wherein the user-side communication property text keyword data comprises cash, bank cards, balances, transfer accounts, money, deposit accounts, bonds, stocks, futures, options, foreign exchange, insurance, trusted products, funds and net credits;
s72, adopting a data search algorithm to communicate text characteristic data between the user and the incoming contact Communicating property text keyword data set/>, with the user sideCommunication property text keyword data/>, of user sideMatching the communication text property keywords of the user and the incoming contact, and generating communication fraud risk identification data/>, of the user and the incoming contact, according to the matching result of the communication text property keywords of the user and the incoming contact;
When (when)And/>Successfully matching the property keywords of the communication text of the user and the incoming contact, and outputting identification data/>, wherein the identification data is used for identifying the fraud risk of the communication of the user and the incoming contact when the property is related to the communication process of the user and the incoming contactTo present a risk of fraud;
When (when) And/>The communication text property keyword of the user and the incoming contact person is not successfully matched, the fact that the property is not involved in the communication process of the user and the incoming contact person is indicated, and then the fraud risk identification data/>, of the user and the incoming contact person, is outputTo be free of fraud risk;
s73, when the user communicates fraud risk identification data with the incoming contact In order to ensure that the user and the incoming contact are respectively communicated with fraud risk identification data/>, when fraud risk existsThe facial feature image data/>, of the incoming contact person are fed back to the user side through the user side communication platform to execute anti-fraud feedback reminding operationAnd feeding back the anti-fraud feedback warning operation to the incoming contact terminal through the communication platform.
The intelligent user information protection anti-fraud system for realizing the intelligent user information protection anti-fraud method comprises an anti-fraud user side communication platform management module, an anti-fraud user side incoming call contact management module and an anti-fraud warning management module;
The anti-fraud user side communication platform management module comprises a user side communication platform characteristic image acquisition unit, a user side communication platform type characteristic image storage unit, a user side communication platform type identification unit and a user side communication platform type identification result output unit;
The user side communication platform characteristic image acquisition unit acquires the user side communication platform characteristic image data through screenshot software; the user side communication platform type characteristic image storage unit is used for storing user side communication platform type characteristic image data; the user side communication platform type identification unit is used for carrying out image characteristic matching of the user side communication platform on the user side communication platform characteristic image data and the user side communication platform type characteristic image data by adopting a data identification algorithm, and analyzing the user side communication platform type data according to an image characteristic matching result of the user side communication platform; the user side communication platform type identification result output unit is used for outputting user side communication platform type data;
The anti-fraud user side incoming call contact management module comprises a user side communication platform stored contact information acquisition unit, a user side communication platform incoming call contact information acquisition unit, a crowd relation type primary judgment unit between a user and an incoming call contact, a last historical communication time point acquisition unit between the user and the incoming call contact, a current communication time point acquisition unit between the user and the incoming call contact, a communication interval time period metering unit between the user and the incoming call contact, a reasonable interval time period storage unit between the user and the incoming call contact, and a crowd relation type secondary judgment unit between the user and the incoming call contact;
The user side communication platform stored contact information acquisition unit searches the user side communication platform stored contact information according to the user side communication platform type data by adopting a data search algorithm; the user side communication platform incoming call contact information acquisition unit acquires the incoming call contact information of the user side communication platform through the user side communication platform; the primary judgment unit of the crowd relation type between the user and the incoming call contact person adopts a data search algorithm to match the incoming call contact person contact data of the user side communication platform with the contact person contact data stored by the user side communication platform to carry out contact person contact data matching of the user side communication platform, and generates primary judgment result data of the crowd relation type between the user and the incoming call contact person according to a contact person contact data matching result of the user side communication platform; the user terminal communication platform is used for acquiring the last historical communication time point data of the user and the incoming contact; the user side communication platform acquires current communication time point data of the user and the incoming call contact; the user and incoming contact person communication interval time period metering unit meters out the user and incoming contact person communication interval time period data according to the last historical communication time point data of the user and the incoming contact person and the current communication time point data of the user and the incoming contact person; the reasonable interval time period storage unit is used for storing reasonable interval time period data of the communication between the user and the incoming contact; the crowd relation type secondary judging unit is used for comparing the communication interval time period data of the user and the incoming call contact with the communication reasonable interval time period data of the user and the incoming call contact by adopting a data searching algorithm, and generating secondary judging result data of the crowd relation type of the user and the incoming call contact according to the comparison result of the communication interval time period data of the user and the incoming call contact;
The anti-fraud warning management module comprises an incoming call contact facial feature image acquisition unit, a user and incoming call contact communication text information acquisition unit, a user side communication property text keyword storage unit, a user and incoming call contact fraud risk identification unit, a user side and incoming call contact side anti-fraud warning unit;
The incoming call contact person facial feature image acquisition unit acquires the incoming call contact person facial feature image data through the mobile terminal shooting lens; the user and incoming call contact person communication text information acquisition unit acquires user and incoming call contact person communication text feature data through a user side communication platform; the user side communication property text keyword storage unit is used for storing user side communication property text keyword data; the user and incoming call contact fraud risk identification unit adopts a data search algorithm to match the communication text characteristic data of the user and incoming call contact with the communication text keyword data of the user end to carry out the communication text property keyword matching of the user and the incoming call contact, and generates the communication fraud risk identification data of the user and the incoming call contact according to the communication text property keyword matching result of the user and the incoming call contact; and the anti-fraud feedback warning unit of the user side and the incoming contact side executes anti-fraud feedback warning operation according to the identification data of the communication fraud risk of the user and the incoming contact.
(III) beneficial effects
The invention provides an intelligent user information protection anti-fraud system and method. The beneficial effects are as follows:
1. The method comprises the steps of acquiring characteristic image parameters of a communication platform used by a user on line through screenshot software by a characteristic image acquisition unit of the communication platform at a user side, and providing data support for accurately identifying the type of the communication platform used by the user; the user side communication platform type characteristic image storage unit presets user side communication platform type characteristic image parameters, and ensures that the anti-fraud system efficiently and accurately judges the type object of the communication platform used by the user; and the user side communication platform type identification unit performs image feature matching on the user side communication platform characteristic image parameters and the user side communication platform type characteristic image parameters by adopting an intelligent identification algorithm, so that the online intelligent identification of the user side communication platform type of the anti-fraud system is realized, and the efficiency of user information protection processing is improved.
2. The user-side communication platform stored contact person information acquisition unit, the user-side communication platform incoming call contact person information acquisition unit and the one-time judgment unit of the crowd relation type between the user and the incoming call contact person are mutually matched, so that the contact person contact parameter between the user and the user-side communication platform stored contact person by combining the communication platform protected contact person information with the intelligent search algorithm is accurately acquired, and the crowd relation type between the user and the incoming call contact person which are strangers or people to be familiar is scientifically judged; the system comprises a last historical communication time point acquisition unit of a user and an incoming contact, a current communication time point acquisition unit of the user and the incoming contact, a communication interval time period metering unit of the user and the incoming contact, a communication reasonable interval time period storage unit of the user and the incoming contact, and a crowd relation type secondary judgment unit between the user and the incoming contact, wherein an intelligent search algorithm is adopted to conduct time period numerical comparison on a communication interval time period parameter of the user and the incoming contact and a communication reasonable interval time period parameter of the user and the incoming contact, and the intelligent judgment is carried out to scientifically and finely divide the user and the incoming contact into a historical familiarity or a normal familiarity crowd relation type under the state that the user and the incoming contact are to-be-determined crowd relation types, so that the system is flexible and accurately adopts different user information protection anti-fraud modes according to different crowd relations of the user and the incoming contact; the identification accuracy of the user information protection anti-fraud system is improved.
3. The facial feature image parameters of strangers or historic familiarity are acquired and backed up by the facial feature image acquisition unit of the incoming call contact person by adopting the mobile terminal shooting lens, so that the safety of a user information protection anti-fraud system is improved; the user and incoming contact communication text information acquisition unit and the user and incoming contact fraud risk identification unit are mutually matched, communication text property key words are matched with scientifically preset user side communication property text key word parameters based on an intelligent search algorithm, intelligent identification of property fraud risk events in the communication process of the user and the incoming contact is realized, and reliability of user information protection is improved; and the anti-fraud warning unit at the user side and the incoming contact side realizes autonomous online feedback warning of the user and the incoming contact, and reduces the risk of fraud caused by information leakage of the user.
Drawings
FIG. 1 is a schematic diagram of a system for protecting intelligent user information against fraud;
Fig. 2 is a flow chart of an anti-fraud method for protecting intelligent user information.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the anti-fraud system and the method for protecting the intelligent user information is as follows:
Referring to fig. 1-2, an anti-fraud method for protecting intelligent user information includes the following steps:
S1, acquiring characteristic image data of a communication platform of a user side;
s2, matching the image characteristics of the user side communication platform with the image characteristics of the user side communication platform type by adopting a data identification algorithm, analyzing the user side communication platform type data according to the image characteristics matching result of the user side communication platform and outputting the data;
S3, searching out a user side communication platform according to the type data of the user side communication platform by adopting a data searching algorithm and storing contact person contact data in the corresponding user side communication platform; collecting contact data of incoming call contacts of a user communication platform;
S4, matching the contact person contact data of the incoming call of the user side communication platform with the contact person contact data stored in the user side communication platform by adopting a data search algorithm, and generating one-time judgment result data of the relationship type between the user and the incoming call contact person group according to the contact person contact data matching result of the user side communication platform;
S5, when the primary judgment result data of the relationship type of the user and the incoming contact person group is a pending familiarity, collecting the last historical communication time point data of the user and the incoming contact person, and the current communication time point data of the user and the incoming contact person; measuring the communication interval time period data of the user and the incoming contact according to the last historical communication time point data of the user and the incoming contact and the current communication time point data of the user and the incoming contact; the data search algorithm is adopted to compare the communication interval time period data of the user and the incoming call contact person with the communication interval time period data of the reasonable communication interval time period data of the user and the incoming call contact person, and secondary judgment result data of the relationship type between the user and the incoming call contact person group is generated according to the comparison result of the communication interval time period data of the user and the incoming call contact person;
S6, collecting facial feature image data of the incoming contact person when primary judgment result data of the relationship type between the user and the incoming contact person is a stranger or secondary judgment result data of the relationship type between the user and the incoming contact person is a historical familiarity, and communicating text feature data between the user and the incoming contact person;
And S7, matching the communication text characteristic data of the user and the incoming contact with the communication text keyword data of the user side by adopting a data search algorithm, generating communication fraud risk identification data of the user and the incoming contact according to the communication text keyword matching result of the user and the incoming contact, and executing anti-fraud feedback warning operation according to the communication fraud risk identification data of the user and the incoming contact.
Further, referring to fig. 1-2, the operation steps for collecting the feature image data of the user side communication platform are as follows:
characteristic image data of a user side communication platform use interface is collected online through screen capturing software and characteristic image data of the user side communication platform are generated The screen capturing software comprises FastStoneCapture, a screen recording screenshot eidolon and ShareX, lightshot, and the user side communication platform comprises any one of QQ, weChat, MOMO, easily trusted and mobile phone call.
The method comprises the following steps of performing image feature matching of a user side communication platform by adopting a data identification algorithm on the user side communication platform feature image data and the user side communication platform type feature image data, analyzing the user side communication platform type data according to the image feature matching result of the user side communication platform, and outputting the user side communication platform type data:
s21, establishing a user communication platform type characteristic image data set ,; Wherein/>Represents the/>Type characteristic image data of user side communication platform corresponding to user side communication platformA maximum value representing the number of types of the communication platform at the user side;
s22, adopting a data recognition algorithm to carry out characteristic image data of the user side communication platform Communication platform type characteristic image data set/>, with userType characteristic image data/>, of medium user terminal communication platformImage feature matching of the user side communication platform is carried out, and the specific operation steps of executing the image feature matching of the user side communication platform by the data identification algorithm are as follows:
s221, initializing parameters, and updating the maximum iteration times T of an algorithm;
s222, initializing the position of the sea-gull population, namely updating the type characteristic image data set of the communication platform in the user by the sea-gull population Searching for a location in the space;
s223, calculating a fitness value and reserving a global optimal position;
s224, migration and global search: the migratory behavior of the seagulls mainly comprises three steps, namely, collision avoidance conditions are required to be met, and population diversity is ensured; a second direction in which the optimal position is to be calculated; thirdly, moving to a new position according to the direction of the optimal position;
s2241, calculating type characteristic image data set of communication platform of seagull at user side New position/>, without collision with adjacent seagulls during motion in search space;
,/>Wherein/>Communication platform type characteristic image data set/>, at user terminal, for seagullSearching for a current location in the space; /(I)The current iteration number; /(I)Communication platform type characteristic image data set/>, at user terminal, for seagullMotion behavior in the search space; /(I)To control/>A function of the variation frequency;
s2242, calculate the direction of the best position ;/>,Wherein/>Representing feature image data/>, of communication platform with user sideMost matched user side communication platform type characteristic image data/>Communication platform type characteristic image data set/>, at userCurrent best position in search space,/>Communication platform type characteristic image data set/>, at user terminal, for seagullSearching for a current location in the space; /(I)Random numbers to balance global and local search capabilities; /(I)A random number in a value [0,1] interval;
S2243, move to new position according to direction of the best position ,
I.e. according to the direction of the optimal position, the type characteristic image data set/>, of the communication platform at the user sideSearching type characteristic image data/>, of a user side communication platform, in the search spaceIs a new location of (2);
S225, attacking the prey, searching locally, and performing spiral movement in the air when the seagull attacks the prey, wherein the new position is after the seagull attacks the prey ,/>I.e. seagull at user terminal communication platform type characteristic image data set/>The characteristic image data/>, of the communication platform at the user side, is displayed in the search spaceCommunication platform type characteristic image data/>, with user sideImage feature matching of the user side communication platform is carried out, and image data/>, which is characteristic of the user side communication platform, is searched outMatched user side communication platform type characteristic image data/>Corresponding prey;
s226, when the maximum iteration times are met, outputting the characteristic image data of the communication platform of the user side Matched user side communication platform type characteristic image data/>Image matching results of (a); otherwise, returning to the step S223;
S23, outputting all user side communication platform characteristic image data according to the step S226 Matched user side communication platform type characteristic image data/>Generating user side communication platform type data/>And output.
The method comprises the steps of acquiring characteristic image parameters of a communication platform used by a user on line through screenshot software by a characteristic image acquisition unit of the communication platform at a user side, and providing data support for accurately identifying the type of the communication platform used by the user; the user side communication platform type characteristic image storage unit presets user side communication platform type characteristic image parameters, and ensures that the anti-fraud system efficiently and accurately judges the type object of the communication platform used by the user; and the user side communication platform type identification unit performs image feature matching on the user side communication platform characteristic image parameters and the user side communication platform type characteristic image parameters by adopting an intelligent identification algorithm, so that the online intelligent identification of the user side communication platform type of the anti-fraud system is realized, and the efficiency of user information protection processing is improved.
Further, referring to fig. 1-2, a data search algorithm is adopted to search out a user side communication platform according to user side communication platform type data and store contact person contact data in a corresponding user side communication platform; the operation steps for collecting the contact data of the incoming call contact person of the user communication platform are as follows:
s31, adopting a breadth-first search algorithm to carry out data according to the type of the communication platform of the user side Searching contact person contact data stored in a user side communication platform in a corresponding user side communication platform, generating a contact person contact data set/>, stored in the user side communication platform, and storing the contact person contact data set/>,/>; Wherein/>Represents the/>The personal user communication platform stores contact person contact data,/>The method comprises the steps of representing the maximum value of the number of the saved contacts of a user side communication platform, wherein the saved contact data of the user side communication platform comprises a communication platform account number and a communication platform name of the saved contacts;
S32, collecting contact data of incoming contact persons of the user side communication platform through the user side communication platform and generating contact data of the incoming contact persons of the user side communication platform The incoming contact data of the user side communication platform comprises a communication platform account number and a communication platform name of the incoming contact.
The method comprises the following steps of adopting a data search algorithm to match the contact person contact data of a user side communication platform with the contact person contact data stored in the user side communication platform to carry out contact person contact data matching of the user side communication platform, and generating one-time judgment result data of the relationship type between a user and an incoming contact person group according to the contact person contact data matching result of the user side communication platform:
adopting a unified cost search algorithm to contact data of incoming calls of a user communication platform Storing contact person contact data set/>, with user communication platformThe medium-user communication platform stores contact person contact data/>Matching contact person contact data of the user side communication platform, and generating one-time judging result data/>, of the relationship type of the user and the incoming contact person group, according to the contact person contact data matching result of the user side communication platform;
When (when)And/>Successfully matching contact data of contacts of the user side communication platform, indicating that the incoming contact belongs to the contacts stored by the user side communication platform, and outputting one-time judging result data/>, of the relationship types of the user and the incoming contact groupIs a pending familiar person;
When (when) And/>The contact person contact data of the user side communication platform is successfully matched, the fact that the incoming contact person does not belong to the contact person stored in the user side communication platform is indicated, and one-time judging result data/>, of the relationship type between the user and the incoming contact person group, is outputIs a stranger.
When the primary judgment result data of the relationship type between the user and the incoming contact person group is a to-be-determined familiar person, collecting the last historical communication time point data of the user and the incoming contact person, and the current communication time point data of the user and the incoming contact person; measuring the communication interval time period data of the user and the incoming contact according to the last historical communication time point data of the user and the incoming contact and the current communication time point data of the user and the incoming contact; the data search algorithm is adopted to compare the communication interval time period data of the user and the incoming call contact person with the communication interval time period data of the reasonable communication interval time period data of the user and the incoming call contact person, and the operation steps of generating secondary judgment result data of the relationship type between the user and the incoming call contact person group according to the comparison result of the communication interval time period data of the user and the incoming call contact person are as follows:
s51, one-time judging result data of relationship type between user and incoming contact person group When the user is a to-be-determined person, acquiring a time point of last historical communication between the user and the incoming contact person through a user side communication platform and generating data/>, of the time point of last historical communication between the user and the incoming contact personWherein/>The unit consists of year, month, day and time;
collecting the current communication time point of the user and the incoming contact person through a user side communication platform and generating the current communication time point data of the user and the incoming contact person Wherein/>The unit consists of year, month, day and time;
s52, according to the last historical communication time point data of the user and the incoming contact And the current communication time point data/>, of the user and the incoming contact personMeasuring data/>, of communication interval time period between user and incoming contact person, by combining time difference measurement formulaWherein/>The unit is h;
S53, establishing reasonable interval time period data for communication between user and incoming contact The data of the reasonable interval time period of the communication between the user and the incoming contact person represent the minimum value of the normal communication time length of the relationship between the user and the incoming contact person belonging to the familiar crowd;
s54, adopting a unified cost search algorithm to communicate interval time period data between the user and the incoming contact Reasonable interval time period data/>, communicated with user and incoming contactPerforming communication interval time period numerical comparison of the user and the incoming call contact person, and generating secondary judging result data/>, of the relationship type of the user and the incoming call contact person group, according to the communication interval time period numerical comparison result of the user and the incoming call contact person;
When (when)≥/>If the communication time length of the user and the incoming contact person is not less than the minimum value of the normal communication time length belonging to the familiar crowd relationship, outputting one-time judging result data/>, of the relationship type of the user and the incoming contact person groupThe user information anti-fraud detection operation is finished for normal familiarity;
When (when) </>If the communication time length of the user and the incoming contact person is smaller than the minimum value of the normal communication time length belonging to the familiar crowd relationship, outputting one-time judging result data/>, of the relationship type of the user and the incoming contact person groupIs a historic familiar person.
The user-side communication platform stored contact person information acquisition unit, the user-side communication platform incoming call contact person information acquisition unit and the one-time judgment unit of the crowd relation type between the user and the incoming call contact person are mutually matched, so that the contact person contact parameter between the user and the user-side communication platform stored contact person by combining the communication platform protected contact person information with the intelligent search algorithm is accurately acquired, and the crowd relation type between the user and the incoming call contact person which are strangers or people to be familiar is scientifically judged; the system comprises a last historical communication time point acquisition unit of a user and an incoming contact, a current communication time point acquisition unit of the user and the incoming contact, a communication interval time period metering unit of the user and the incoming contact, a communication reasonable interval time period storage unit of the user and the incoming contact, and a crowd relation type secondary judgment unit between the user and the incoming contact, wherein an intelligent search algorithm is adopted to conduct time period numerical comparison on a communication interval time period parameter of the user and the incoming contact and a communication reasonable interval time period parameter of the user and the incoming contact, and the intelligent judgment is carried out to scientifically and finely divide the user and the incoming contact into a historical familiarity or a normal familiarity crowd relation type under the state that the user and the incoming contact are to-be-determined crowd relation types, so that the system is flexible and accurately adopts different user information protection anti-fraud modes according to different crowd relations of the user and the incoming contact; the identification accuracy of the user information protection anti-fraud system is improved.
Further, referring to fig. 1-2, when the primary judgment result data of the relationship type between the user and the incoming contact person is a stranger or the secondary judgment result data of the relationship type between the user and the incoming contact person is a history familiarity, facial feature image data of the incoming contact person are collected, and the operation steps of the text feature data of the communication between the user and the incoming contact person are as follows:
When the relationship type between the user and the incoming contact person group is judged at one time, the result data is obtained One-time judging result data/>, for strangers or relationship types of users and incoming contact groupsWhen the mobile terminal shooting lens is a historical familiarity, the mobile terminal shooting lens is used for collecting facial feature images of the incoming contact person and generating facial feature image data/>;
Collecting text data of communication voice between a user and an incoming contact person through a user side communication platform and generating text characteristic data of communication between the user and the incoming contact person。
The method comprises the following steps of adopting a data search algorithm to match the communication text characteristic data of the user and the incoming contact with the communication text property keyword data of the user side to carry out the communication text property keyword matching of the user and the incoming contact, generating the communication fraud risk identification data of the user and the incoming contact according to the communication text property keyword matching result of the user and the incoming contact, and executing anti-fraud feedback warning operation according to the communication fraud risk identification data of the user and the incoming contact:
S71, establishing a user communication property text keyword data set ,; Wherein/>Represents the/>Personal user side communication property text keyword data,/>Representing a maximum value of the number of the user-side communication property text keyword data, wherein the user-side communication property text keyword data comprises cash, bank cards, balances, transfer accounts, money, deposit, bonds, stocks, futures, options, foreign exchange, insurance, trusted products, funds and net credits;
s72, adopting a data search algorithm to communicate text characteristic data between the user and the incoming contact Communicating property text keyword data set/>, with a user terminalCommunication property text keyword data/>, of user sideMatching the communication text property keywords of the user and the incoming contact, and generating communication fraud risk identification data/>, of the user and the incoming contact, according to the matching result of the communication text property keywords of the user and the incoming contact;
When (when)And/>Successfully matching the property keywords of the communication text of the user and the incoming contact, and outputting identification data/>, wherein the identification data is used for identifying the fraud risk of the communication of the user and the incoming contact when the property is related to the communication process of the user and the incoming contactTo present a risk of fraud;
When (when) And/>The communication text property keyword of the user and the incoming contact person is not successfully matched, the fact that the property is not involved in the communication process of the user and the incoming contact person is indicated, and then the fraud risk identification data/>, of the user and the incoming contact person, is outputTo be free of fraud risk;
s73, when the user communicates fraud risk identification data with the incoming contact In order to ensure that the fraud risk exists, the fraud risk identification data/>, which are respectively communicated between the user and the incoming contact personThe anti-fraud feedback reminding operation is carried out by feeding back the facial feature image data/>, which are connected with the human facial feature image data, to the user through the user communication platformAnd feeding back the anti-fraud feedback warning operation to the incoming contact terminal through the communication platform.
The facial feature image parameters of strangers or historic familiarity are acquired and backed up by the facial feature image acquisition unit of the incoming call contact person by adopting the mobile terminal shooting lens, so that the safety of a user information protection anti-fraud system is improved; the user and incoming contact communication text information acquisition unit and the user and incoming contact fraud risk identification unit are mutually matched, communication text property key words are matched with scientifically preset user side communication property text key word parameters based on an intelligent search algorithm, intelligent identification of property fraud risk events in the communication process of the user and the incoming contact is realized, and reliability of user information protection is improved; and the anti-fraud warning unit at the user side and the incoming contact side realizes autonomous online feedback warning of the user and the incoming contact, and reduces the risk of fraud caused by information leakage of the user.
An intelligent user information protection anti-fraud system for realizing an intelligent user information protection anti-fraud method comprises an anti-fraud user side communication platform management module, an anti-fraud user side incoming call contact management module and an anti-fraud warning management module;
The anti-fraud user side communication platform management module comprises a user side communication platform characteristic image acquisition unit, a user side communication platform type characteristic image storage unit, a user side communication platform type identification unit and a user side communication platform type identification result output unit;
The user side communication platform characteristic image acquisition unit acquires the user side communication platform characteristic image data through screenshot software; the user side communication platform type characteristic image storage unit is used for storing user side communication platform type characteristic image data; the user side communication platform type identification unit is used for carrying out image characteristic matching of the user side communication platform on the user side communication platform characteristic image data and the user side communication platform type characteristic image data by adopting a data identification algorithm, and analyzing the user side communication platform type data according to the image characteristic matching result of the user side communication platform; the user side communication platform type identification result output unit is used for outputting user side communication platform type data;
The anti-fraud user side incoming call contact management module comprises a user side communication platform stored contact information acquisition unit, a user side communication platform incoming call contact information acquisition unit, a crowd relation type primary judgment unit between a user and an incoming call contact, a last historical communication time point acquisition unit between the user and the incoming call contact, a current communication time point acquisition unit between the user and the incoming call contact, a communication interval time period metering unit between the user and the incoming call contact, a reasonable interval time period storage unit between the user and the incoming call contact, and a crowd relation type secondary judgment unit between the user and the incoming call contact;
The user side communication platform stored contact information acquisition unit searches the user side communication platform stored contact information according to the type data of the user side communication platform by adopting a data search algorithm; the user side communication platform incoming call contact information acquisition unit acquires incoming call contact data of the user side communication platform through the user side communication platform; the first judgment unit of the crowd relation type between the user and the incoming contact person adopts a data search algorithm to match the incoming contact person contact data of the user side communication platform with the contact person contact data stored by the user side communication platform to carry out contact person contact data matching of the user side communication platform, and generates first judgment result data of the crowd relation type between the user and the incoming contact person according to the contact person contact data matching result of the user side communication platform; the user terminal communication platform is used for acquiring historical communication time point data of the user and the incoming contact person last time; the user side communication platform acquires the current communication time point data of the user and the incoming contact; the user and incoming contact person communication interval time period metering unit meters out the user and incoming contact person communication interval time period data according to the last historical communication time point data of the user and the incoming contact person and the current communication time point data of the user and the incoming contact person; the user and incoming contact person communication reasonable interval time period storage unit is used for storing user and incoming contact person communication reasonable interval time period data; the crowd relation type secondary judging unit between the user and the incoming call contact adopts a data searching algorithm to compare the communication interval time period data of the user and the incoming call contact with the communication reasonable interval time period data of the user and the incoming call contact, and generates secondary judging result data of the crowd relation type of the user and the incoming call contact according to the comparison result of the communication interval time period data of the user and the incoming call contact;
the anti-fraud warning management module comprises an incoming call contact facial feature image acquisition unit, a user and incoming call contact communication text information acquisition unit, a user communication property text keyword storage unit, a user and incoming call contact fraud risk identification unit, and a user side and incoming call contact side anti-fraud warning unit;
The mobile terminal shooting lens is used for shooting the face characteristic image data of the incoming contact person; the user and incoming contact person communication text information acquisition unit acquires user and incoming contact person communication text feature data through a user side communication platform; the user side communication property text keyword storage unit is used for storing user side communication property text keyword data; the user and incoming contact fraud risk identification unit is used for matching the communication text characteristic data of the user and the incoming contact with the communication text keyword data of the user terminal by adopting a data search algorithm, and generating the communication fraud risk identification data of the user and the incoming contact according to the communication text keyword matching result of the user and the incoming contact; and the anti-fraud feedback warning unit is used for executing anti-fraud feedback warning operation according to the communication fraud risk identification data of the user and the incoming contact.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. An anti-fraud method for intelligent user information protection, characterized in that the method comprises the following steps:
S1, acquiring characteristic image data of a communication platform of a user side;
S2, matching the image characteristics of the user side communication platform with the image characteristics of the user side communication platform type by adopting a data identification algorithm, analyzing the user side communication platform type data according to the image characteristics matching result of the user side communication platform and outputting the data;
S3, searching out a user side communication platform according to the type data of the user side communication platform by adopting a data searching algorithm and storing contact person contact data in the corresponding user side communication platform; collecting contact data of incoming call contacts of a user communication platform;
S4, matching the contact person contact data of the user side communication platform with the contact person contact data stored in the user side communication platform by adopting a data search algorithm, and generating primary judgment result data of the relationship type between the user and the incoming contact person group according to the contact person contact data matching result of the user side communication platform;
S5, when the primary judgment result data of the relationship type of the user and the incoming contact person group is a to-be-determined familiarity, collecting the last historical communication time point data of the user and the incoming contact person, and the current communication time point data of the user and the incoming contact person; measuring the communication interval time period data of the user and the incoming call contact according to the last historical communication time point data of the user and the incoming call contact and the current communication time point data of the user and the incoming call contact; the data search algorithm is adopted to compare the communication interval time period data of the user and the incoming call contact person with the communication interval time period data of the reasonable communication interval time period data of the user and the incoming call contact person, and secondary judgment result data of the relationship type between the user and the incoming call contact person group is generated according to the comparison result of the communication interval time period data of the user and the incoming call contact person;
S6, collecting facial feature image data of the incoming contact person when the primary judgment result data of the relationship type between the user and the incoming contact person is a stranger or the secondary judgment result data of the relationship type between the user and the incoming contact person is a historical familiar person, and communicating text feature data between the user and the incoming contact person;
and S7, matching the communication text characteristic data of the user and the incoming contact with the communication text keyword data of the user terminal by adopting a data search algorithm, generating communication fraud risk identification data of the user and the incoming contact according to a matching result of the communication text keyword of the user and the incoming contact, and executing anti-fraud feedback warning operation according to the communication fraud risk identification data of the user and the incoming contact.
2. An intelligent user information protection anti-fraud method according to claim 1, characterized in that: the step S1 comprises the following steps:
characteristic image data of a user side communication platform use interface is collected online through screen capturing software and characteristic image data of the user side communication platform are generated The screen capturing software comprises FastStoneCapture, a screen recording screenshot eidolon and ShareX, lightshot, and the client communication platform comprises any one of QQ, weChat, MOMO, easily trusted and mobile phone call.
3. An anti-fraud method for intelligent user information protection according to claim 2, characterized in that: the step S2 comprises the following steps:
s21, establishing a user communication platform type characteristic image data set ,; Wherein/>Represents the/>Type characteristic image data of user side communication platform corresponding to user side communication platformA maximum value representing the number of types of the communication platform at the user side;
S22, adopting a data recognition algorithm to carry out characteristic image data of the user side communication platform Communication platform type characteristic image data set/>, with the user sideType characteristic image data/>, of medium user terminal communication platformImage feature matching of the user side communication platform is carried out, and the specific operation steps of executing the image feature matching of the user side communication platform by the data identification algorithm are as follows:
s221, initializing parameters, and updating the maximum iteration times T of an algorithm;
s222, initializing the position of the sea-gull population, namely updating the type characteristic image data set of the communication platform in the user by the sea-gull population Searching for a location in the space;
s223, calculating a fitness value and reserving a global optimal position;
s224, migration and global search: the migratory behavior of the seagulls mainly comprises three steps, namely, collision avoidance conditions are required to be met, and population diversity is ensured; a second direction in which the optimal position is to be calculated; thirdly, moving to a new position according to the direction of the optimal position;
s2241, calculating type characteristic image data set of communication platform of seagull at user side New position/>, without collision with adjacent seagulls during motion in search space;
,/>Wherein/>Communication platform type characteristic image data set/>, at user terminal, for seagullSearching for a current location in the space; /(I)The current iteration number; /(I)Communication platform type characteristic image data set/>, at user terminal, for seagullMotion behavior in the search space; /(I)To control/>A function of the variation frequency;
s2242, calculate the direction of the best position ;
S2243, move to new position according to direction of the best positionI.e. according to the direction of the optimal position, the type characteristic image data set/>, of the communication platform at the user sideSearching type characteristic image data/>, of a user side communication platform, in the search spaceIs a new location of (2);
S225, attacking the prey, searching locally, and performing spiral movement in the air when the seagull attacks the prey, wherein the new position is after the seagull attacks the prey I.e. seagull at user terminal communication platform type characteristic image data set/>The characteristic image data/>, of the communication platform at the user side, is displayed in the search spaceCommunication platform type characteristic image data/>, with user sideImage feature matching of the user side communication platform is carried out, and image data/>, which is characteristic of the user side communication platform, is searched outMatched user side communication platform type characteristic image data/>Corresponding prey;
s226, when the maximum iteration times are met, outputting the characteristic image data of the communication platform of the user side Matched user side communication platform type characteristic image data/>Image matching results of (a); otherwise, returning to the step S223;
S23, outputting all user side communication platform characteristic image data according to the step S226 Matched user side communication platform type characteristic image data/>Generating user side communication platform type data/>And output.
4. A method of anti-fraud for intelligent user information protection according to claim 3, characterized by: the step S3 comprises the following steps:
S31, adopting a breadth-first search algorithm to obtain the type data of the user side communication platform Searching contact person contact data stored in a user side communication platform in a corresponding user side communication platform, generating a contact person contact data set/>, stored in the user side communication platform, and storing the contact person contact data set/>,/>; Wherein/>Represents the/>The personal user communication platform stores contact person contact data,/>The method comprises the steps of representing the maximum value of the number of the saved contacts of a user side communication platform, wherein the saved contact data of the user side communication platform comprises a communication platform account number and a communication platform name of the saved contacts;
S32, collecting contact data of incoming contact persons of the user side communication platform through the user side communication platform and generating contact data of the incoming contact persons of the user side communication platform The incoming contact data of the user side communication platform comprise a communication platform account number and a communication platform name of the incoming contact.
5. The anti-fraud method for intelligent user information protection of claim 4, wherein: the step S4 comprises the following steps:
adopting a unified cost search algorithm to enable incoming call contact person contact data of the user communication platform Storing contact person contact data set/>, with the user side communication platformThe medium-user communication platform stores contact person contact data/>Matching contact person contact data of the user side communication platform, and generating one-time judging result data/>, of the relationship type of the user and the incoming contact person group, according to the contact person contact data matching result of the user side communication platform;
When (when)And/>Successfully matching contact data of contacts of the user side communication platform, indicating that the incoming contact belongs to the contacts stored by the user side communication platform, and outputting one-time judging result data/>, of the relationship types of the user and the incoming contact groupIs a pending familiar person;
When (when) And/>The contact person contact data of the user side communication platform is successfully matched, the fact that the incoming contact person does not belong to the contact person stored in the user side communication platform is indicated, and one-time judging result data/>, of the relationship type between the user and the incoming contact person group, is outputIs a stranger.
6. The anti-fraud method for intelligent user information protection of claim 5, wherein: the step S5 comprises the following steps:
S51, the user and the incoming contact person group relationship type one-time judgment result data When the user is a to-be-determined person, acquiring a time point of last historical communication between the user and the incoming contact person through a user side communication platform and generating data/>, of the time point of last historical communication between the user and the incoming contact personWherein/>The unit consists of year, month, day and time;
collecting the current communication time point of the user and the incoming contact person through a user side communication platform and generating the current communication time point data of the user and the incoming contact person Wherein/>The unit consists of year, month, day and time;
s52, according to the last historical communication time point data of the user and the incoming contact And the current communication time point data/>, of the user and the incoming contact personMeasuring data/>, of communication interval time period between user and incoming contact person, by combining time difference measurement formulaWherein/>The unit is h;
S53, establishing reasonable interval time period data for communication between user and incoming contact The data of the reasonable interval time period of the communication between the user and the incoming contact represent the minimum value of the normal communication time length of the relationship between the user and the incoming contact belonging to the familiar crowd;
s54, adopting a unified cost search algorithm to communicate interval time period data between the user and the incoming contact Reasonable interval time period data/>, communicated with user and incoming contactPerforming communication interval time period numerical comparison of the user and the incoming call contact person, and generating secondary judging result data/>, of the relationship type of the user and the incoming call contact person group, according to the communication interval time period numerical comparison result of the user and the incoming call contact person;
When (when)≥/>The communication time length of the user and the incoming contact person is not less than the minimum value of the normal communication time length belonging to the familiar crowd relationship, and one-time judgment result data of the relationship type of the user and the incoming contact person is outputThe user information anti-fraud detection operation is finished for normal familiarity;
When (when) </>The communication time length of the user and the incoming contact person is smaller than the minimum value of the normal communication time length belonging to the familiar crowd relationship, and one-time judgment result data of the relationship type of the user and the incoming contact person is outputIs a historic familiar person.
7. The anti-fraud method for intelligent user information protection of claim 6, wherein: the step S6 comprises the following steps:
When the relationship type of the user and the incoming contact person group is judged at one time, the result data is obtained One-time judging result data/>, for strangers or relationship types of the user and incoming contact groupWhen the mobile terminal shooting lens is a historical familiarity, the mobile terminal shooting lens is used for collecting facial feature images of the incoming contact person and generating facial feature image data/>;
Collecting text data of communication voice between a user and an incoming contact person through a user side communication platform and generating text characteristic data of communication between the user and the incoming contact person。
8. The anti-fraud method for intelligent user information protection of claim 7, wherein: the step S7 comprises the following steps:
S71, establishing a user communication property text keyword data set ,; Wherein/>Represents the/>Personal user side communication property text keyword data,/>Representing a maximum value of the number of the user-side communication property text keyword data, wherein the user-side communication property text keyword data comprises cash, bank cards, balances, transfer accounts, money, deposit accounts, bonds, stocks, futures, options, foreign exchange, insurance, trusted products, funds and net credits;
s72, adopting a data search algorithm to communicate text characteristic data between the user and the incoming contact Communicating property text keyword data set/>, with the user sideCommunication property text keyword data/>, of user sideMatching the communication text property keywords of the user and the incoming contact, and generating communication fraud risk identification data/>, of the user and the incoming contact, according to the matching result of the communication text property keywords of the user and the incoming contact;
When (when)And/>Successfully matching the property keywords of the communication text of the user and the incoming contact, and outputting identification data/>, wherein the identification data is used for identifying the fraud risk of the communication of the user and the incoming contact when the property is related to the communication process of the user and the incoming contactTo present a risk of fraud;
When (when) And/>The communication text property keyword of the user and the incoming contact person is not successfully matched, the fact that the property is not involved in the communication process of the user and the incoming contact person is indicated, and then the fraud risk identification data/>, of the user and the incoming contact person, is outputTo be free of fraud risk;
s73, when the user communicates fraud risk identification data with the incoming contact In order to ensure that the user and the incoming contact are respectively communicated with fraud risk identification data/>, when fraud risk existsThe facial feature image data/>, of the incoming contact person are fed back to the user side through the user side communication platform to execute anti-fraud feedback reminding operationAnd feeding back the anti-fraud feedback warning operation to the incoming contact terminal through the communication platform.
9. An intelligent user information protection anti-fraud system implementing an intelligent user information protection anti-fraud method of any of claims 1-8, characterized by: the system comprises a fraud prevention user side communication platform management module, a fraud prevention user side incoming call contact management module and a fraud prevention warning management module.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104253908A (en) * | 2014-09-18 | 2014-12-31 | 北京奇虎科技有限公司 | Unknown number grading method, unknown number marking method and unknown number marking device |
CN106911845A (en) * | 2017-02-21 | 2017-06-30 | 北京小米移动软件有限公司 | Incoming call reminding method and device |
CN109300028A (en) * | 2018-09-11 | 2019-02-01 | 上海天旦网络科技发展有限公司 | Real-time anti-fraud method and system and storage medium based on network data |
CN111080440A (en) * | 2019-12-18 | 2020-04-28 | 上海良鑫网络科技有限公司 | Big data wind control management system |
CN117635174A (en) * | 2023-12-04 | 2024-03-01 | 中国人寿保险股份有限公司山东省分公司 | Fraud risk assessment method and system for comprehensive multi-mode AI analysis |
-
2024
- 2024-04-26 CN CN202410508302.3A patent/CN118096191B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104253908A (en) * | 2014-09-18 | 2014-12-31 | 北京奇虎科技有限公司 | Unknown number grading method, unknown number marking method and unknown number marking device |
CN106911845A (en) * | 2017-02-21 | 2017-06-30 | 北京小米移动软件有限公司 | Incoming call reminding method and device |
CN109300028A (en) * | 2018-09-11 | 2019-02-01 | 上海天旦网络科技发展有限公司 | Real-time anti-fraud method and system and storage medium based on network data |
CN111080440A (en) * | 2019-12-18 | 2020-04-28 | 上海良鑫网络科技有限公司 | Big data wind control management system |
CN117635174A (en) * | 2023-12-04 | 2024-03-01 | 中国人寿保险股份有限公司山东省分公司 | Fraud risk assessment method and system for comprehensive multi-mode AI analysis |
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