CN114733207A - Game account monitoring, analyzing, early warning and managing system based on feature analysis - Google Patents
Game account monitoring, analyzing, early warning and managing system based on feature analysis Download PDFInfo
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- CN114733207A CN114733207A CN202210516167.8A CN202210516167A CN114733207A CN 114733207 A CN114733207 A CN 114733207A CN 202210516167 A CN202210516167 A CN 202210516167A CN 114733207 A CN114733207 A CN 114733207A
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/70—Game security or game management aspects
- A63F13/79—Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/70—Game security or game management aspects
- A63F13/71—Game security or game management aspects using secure communication between game devices and game servers, e.g. by encrypting game data or authenticating players
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention discloses a game account monitoring, analyzing and early warning management system based on characteristic analysis, which contrasts and analyzes the login equipment state of each game account in a target game platform by acquiring the real-time login equipment information of each game account in the target game platform and the normal login equipment information in a preset time period, and performs corresponding processing, thereby effectively ensuring the login safety of the game account of the game platform and reducing the possibility of the game account being stolen; meanwhile, the comprehensive safety factor of each game account in the target game platform is analyzed according to the user behavior parameters of each appointed game account in the target game platform, and corresponding early warning processing is carried out according to the comparison and analysis result, so that the user behavior parameters after the game account logs in are monitored in real time, the virtual property loss of the user corresponding to the game account is reduced, the game experience of the game user is not influenced, and the user loss of the game platform is further avoided.
Description
Technical Field
The invention relates to the field of game account monitoring and analysis, in particular to a game account monitoring, analyzing, early warning and managing system based on feature analysis.
Background
The problem of security of game accounts is the problem faced by all online games. Lawless persons can obtain game account passwords by different means, such as planting trojans on a game user login device, or obtaining the game account passwords by cheating the trust of game users in a game, and after obtaining the game user account passwords, the lawless persons log in the game accounts of the users, steal game account resources of the users and obtain benefits.
At present, in order to ensure the security of game accounts of users, each game platform usually only verifies the correctness of game account IDs and passwords, does not consider whether login equipment of the game accounts is normal login equipment, and has the behavior that lawless persons log in the game accounts through strange equipment to steal resources, so that the login security of the game accounts of the game platform cannot be ensured, the possibility that the game accounts are stolen is further increased, the security supervision level of the game accounts of the users by the game platform is further reduced, and the development of the game platform in the later period is greatly influenced.
Meanwhile, the existing game platform can only carry out safety supervision when a game account logs in, and lacks real-time supervision on user behavior parameters after the game account logs in, so that the existing game platform has certain limitation on safety supervision of the game account, and the problem that the existing game platform cannot timely handle abnormal operation behaviors after part of the game account is stolen exists, so that virtual property loss of a user corresponding to the game account is increased, and further very poor game experience is brought to a game user.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a game account monitoring, analyzing, early warning and managing system based on feature analysis, which has the following specific technical scheme:
a game account monitoring, analyzing and early warning management system based on feature analysis comprises:
a frequently-logged-in equipment information acquisition module: the system comprises a target game platform, a server and a server, wherein the target game platform is used for acquiring historical login equipment information of each game account in the target game platform within a preset time period, and obtaining frequent login equipment information of each game account in the target game platform within the preset time period through comparison;
the game account number login equipment state analysis module: the system comprises a target game platform, a login device and a server, wherein the target game platform is used for acquiring real-time login device information of each game account in the target game platform and comparing and analyzing the login device state of each game account in the target game platform;
the game account login equipment state processing module comprises: the system comprises a target game platform, a login device and a display device, wherein the target game platform is used for logging in each game account;
game platform database: the system comprises a game device, a game system and a game system, wherein the game device is used for storing a user habit login time range and an average online time of a user single-time login game corresponding to each game account in a preset time period, simultaneously storing an average operation time, an average game task operation score, an average game activity participation degree and an average game activity completion degree of each game account in a user single-time login game corresponding to each preset time period, and storing standard market transaction amount corresponding to each game device;
a user behavior parameter acquisition module: the system comprises a target game platform, a user operation behavior parameter and a user transaction behavior parameter, wherein the target game platform is used for acquiring user behavior parameters of each appointed game account in the target game platform, and the user behavior parameters comprise a user login habit behavior parameter, a user operation behavior parameter and a user transaction behavior parameter;
the user behavior parameter analysis module: the system comprises a target game platform, a game server and a game server, wherein the target game platform is used for acquiring user behavior parameters of each appointed game account in the target game platform according to the user behavior parameters of each appointed game account in the target game platform;
the game account comprehensive safety coefficient analysis module comprises: and the comprehensive safety factor analysis module is used for analyzing the comprehensive safety factor of each game account in the target game platform according to the condition that the user behavior parameters of each appointed game account in the target game platform accord with the proportional coefficient, comparing the comprehensive safety factor with a preset standard safety factor threshold value respectively, and performing corresponding early warning processing according to the comparison and analysis result.
On the basis of the above embodiment, the specific acquiring manner corresponding to the frequently-logged-in device information acquiring module is as follows:
extracting information of each historical login device of each game account in a preset time period from a target game platform background, wherein each piece of historical login device information comprises an ip address of each historical login device and an MAC address of each historical login device, counting the historical login times of each ip address and the historical login times of each MAC address of each game account in the target game platform in the preset time period, recording the ip address as the ip address of the frequently-logged device of each game account in the preset time period if the historical login times of a certain ip address of each game account in the target game platform in the preset time period is larger than a preset threshold of the historical login times, and counting the ip address of each frequently-logged device of each game account in the target game platform in the preset time period; similarly, the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are counted, and the ip addresses and the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are recorded as the information of the frequently-logged devices of the game accounts within the preset time period.
On the basis of the above embodiment, the comparing and analyzing, in the game account login device state analysis module, the login device state of each game account in the target game platform specifically includes:
the method comprises the steps of obtaining real-time login equipment information of each game account in a target game platform, comparing the real-time login equipment information of each game account in the target game platform with the frequently-logged-in equipment information of the corresponding game account in a preset time period, and analyzing to obtain the login equipment state of each game account in the target game platform according to a preset game account login equipment state analysis rule, wherein the login equipment state comprises a normal state, a state to be verified and an abnormal state.
On the basis of the above embodiment, the game account login device state processing module performs corresponding processing according to the login device state of each game account in the target game platform, and the specific processing mode is as follows:
according to the login equipment state of each game account in the target game platform, if the login equipment state of a certain game account in the target game platform is a normal state, allowing the login request of the game account; if the login equipment state of a certain game account in the target game platform is a to-be-verified state, notifying an operation user corresponding to the game account to perform number main real-name verification, and allowing the login request of the game account after the number main real-name verification is correct; if the login equipment state of a certain game account in the target game platform is in an abnormal state, informing a game account corresponding number owner to carry out auditing treatment, allowing the login request of the game account after the game account corresponding number owner passes the auditing treatment, and otherwise pulling the real-time login equipment information of the game account into a platform blacklist.
On the basis of the embodiment, the user login habit behavior parameters comprise user login time and user online time; the user operation behavior parameters comprise user operation duration, game task operation scores, game activity participation degrees and game activity completion degrees; the user transaction behavior parameters comprise equipment transaction information and game currency transaction information, wherein the equipment transaction information comprises the number of various transaction equipment and the total equipment transaction amount, and the game currency transaction information comprises the game currency count and the game currency expenditure amount.
On the basis of the above embodiment, the analyzing module for the user behavior parameters, in the target game platform, analyzes that the user behavior parameters of each designated game account conform to the proportionality coefficient, and the specific analysis content includes:
according to the user habit login time range and the average online time of the single-time login game of the user corresponding to each game account in the preset time period stored in the game platform database, extracting the user habit login time range and the average online time of the single-time login game of the user corresponding to each specified game account in the preset time period, comparing the user login time of the user login habit behavior parameter of each specified game account in the target game platform with the user habit login time range of the specified game account in the preset time period to obtain the user login time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform, analyzing the user online time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform according to the user online time of the user login habit behavior parameter of each specified game account in the target game platform, enabling the user login time in the user login habit behavior parameters of each appointed game account in the target game platform to accord with the weight factor and when the user is onlineThe long-coincidence weight factors are respectively marked as deltaia1And deltaia2Where i 1, 2.., n, i denotes the number of the i-th designated game account;
the user login time in the user login habit behavior parameters of each specified game account number in the target game platform is in accordance with the weight factor deltaia1According with the user online time length as a weight factor deltaia2Substituting the user login habit behavior parameters into the formula xi for the analysis of the proportional coefficienti＝λ1*δia1+λ2*δia2Obtaining user login habit behavior parameters of each appointed game account number in the target game platform according with the proportionality coefficient xiiWherein λ is1And λ2Respectively representing the preset user login time and the corresponding correction index of the user online time.
On the basis of the above embodiment, the analyzing, in the user behavior parameter analyzing module, the user behavior parameters of each specified game account in the target game platform conform to the proportionality coefficient, and the specific analysis content further includes:
according to the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of each game account corresponding to the user in the single-login game in the preset time period, which are stored in the game platform database, extracting the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of each appointed game account corresponding to the user in the single-login game in the preset time period, and respectively marking the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of each appointed game account corresponding to the user in the single-login game in the preset time period as the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree
Analyzing the user operation behavior parameters of each appointed game account in the target game platform to accord with the proportional coefficient
Wherein
The user operation behavior parameter expressed as the ith appointed game account number in the target game platform conforms to a proportional coefficient sigma1、σ2、σ3Respectively expressed as corresponding correction indexes, delta p, of operation duration, task operation score and activity participation completion degree in preset user operation behaviorsAllow forb1、ΔpAllow forb3、ΔpAllow forb4Respectively expressed as the preset operation time length allowed error value, game activity participation degree allowed error value, game activity completion degree allowed error value, p of the user single-time login gameib1、pib2、pib3、pib4The game parameters are respectively expressed as the user operation duration, the game task operation score, the game activity participation degree and the game activity completion degree of the user operation behavior parameter of the ith appointed game account in the target game platform, and e is expressed as a natural constant.
On the basis of the above embodiment, the analyzing, by the user behavior parameter analyzing module, that the user behavior parameters of each specified game account in the target game platform conform to the proportionality coefficient further includes:
extracting standard market transaction amount corresponding to each game equipment stored in a game platform database, screening the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in a target game platform, and marking the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in the target game platform as ri jJ is 1,2, and m, j is the number of the jth transaction equipment;
analyzing to obtain user transaction behavior parameters of each appointed game account number in the target game platform according to equipment transaction information and game currency transaction information in the user transaction behavior parameters of each appointed game account number in the target game platform, wherein the user transaction behavior parameters conform to the proportional coefficient
On the basis of the above embodiment, the comprehensive security coefficient of each game account in the target game platform is analyzed in the game account comprehensive security coefficient analysis module, and the specific analysis mode is as follows:
matching the user login habit behavior parameters of each appointed game account number in the target game platform with the proportionality coefficient xiiThe user operation behavior parameters accord with the proportionality coefficient
According with the user transaction behavior parameter
Substitution formula
Obtaining the comprehensive safety factor omega of each game account number in the target game platformiTherein x1、χ2、χ3Respectively expressed as preset safety influence factors corresponding to user login habit behavior, user operation behavior and user transaction behavior, and x1+χ2+χ3＝1。
On the basis of the above embodiment, the early warning processing corresponding to the result of the comparative analysis is performed in the game account comprehensive safety factor analysis module, which specifically includes:
the comprehensive safety factor of each game account in the target game platform is compared with a preset standard safety factor threshold, if the comprehensive safety factor of a certain game account in the target game platform is smaller than the preset standard safety factor threshold, the game account in the target game platform is in a number stealing state, a number stealing early warning prompt is sent to the target game platform, and after the target game platform receives the number stealing early warning prompt sent by the game account, a game account corresponding number owner is informed to carry out emergency processing.
The invention has the technical effects that:
according to the game account monitoring, analyzing and early warning management system based on characteristic analysis, the real-time login equipment information of each game account in the target game platform and the frequent login equipment information in a preset time period are obtained, the login equipment state of each game account in the target game platform is contrastively analyzed, and corresponding processing is carried out according to the login equipment state of each game account in the target game platform, so that the behavior that lawless persons log in the game accounts through strange equipment to steal resources is avoided, the login safety of the game accounts of the game platform is further effectively ensured, the possibility that the game accounts are stolen is reduced, the safety supervision level of the game accounts of users by the game platform is further improved, and the development of the game platform in the later period is greatly promoted.
The invention provides a game account monitoring, analyzing and early warning management system based on characteristic analysis, which obtains user behavior parameters of each appointed game account in a target game platform by obtaining the user behavior parameters of each appointed game account in the target game platform, analyzes the comprehensive safety factor of each appointed game account in the target game platform, compares the comprehensive safety factor with a preset standard safety factor threshold value, and performs corresponding early warning treatment according to the comparison analysis result, thereby realizing real-time supervision on the user behavior parameters after the game account is logged in, breaking the limitation of the existing game platform on the safety supervision of the game account, avoiding the problem that the abnormal operation behavior cannot be processed in time after part of the game accounts are stolen to the greatest extent, further reducing the virtual property loss of users corresponding to the game accounts, and ensuring that the game experience of game users is not influenced, further avoiding the user loss of the game platform.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a system module connection diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides a game account monitoring, analyzing, and early warning management system based on feature analysis, which includes a frequently-logged-in device information acquisition module, a game account logging-in device state analysis module, a game account logging-in device state processing module, a game platform database, a user behavior parameter acquisition module, a user behavior parameter analysis module, and a game account comprehensive safety factor analysis module.
The game system comprises a game platform database, a game account login device state analysis module, a user behavior parameter acquisition module, a game account login device state processing module, a user behavior parameter analysis module and a game platform comprehensive safety factor analysis module.
The frequently-logged-in equipment information acquisition module is used for acquiring the historical logged-in equipment information of each game account in the target game platform within a preset time period, and comparing the historical logged-in equipment information with the historical logged-in equipment information of each game account in the target game platform within the preset time period.
As a preferred scheme, the specific corresponding acquiring manner in the frequently-logged device information acquiring module is as follows:
extracting information of each historical login device of each game account in a preset time period from a target game platform background, wherein each piece of historical login device information comprises an ip address of each historical login device and an MAC address of each historical login device, counting the historical login times of each ip address and the historical login times of each MAC address of each game account in the target game platform in the preset time period, recording the ip address as the ip address of the frequently-logged device of each game account in the preset time period if the historical login times of a certain ip address of each game account in the target game platform in the preset time period is larger than a preset threshold of the historical login times, and counting the ip address of each frequently-logged device of each game account in the target game platform in the preset time period; similarly, the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are counted, and the ip addresses and the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are recorded as the information of the frequently-logged devices of the game accounts within the preset time period.
The game account login equipment state analysis module is used for acquiring real-time login equipment information of each game account in the target game platform, and comparing and analyzing the login equipment state of each game account in the target game platform.
As a preferred scheme, the comparing and analyzing module for the states of the login devices of the game accounts in the target game platform specifically includes:
the method comprises the steps of obtaining real-time login equipment information of each game account in a target game platform, comparing the real-time login equipment information of each game account in the target game platform with the frequently-logged-in equipment information of the corresponding game account in a preset time period, and analyzing to obtain the login equipment state of each game account in the target game platform according to a preset game account login equipment state analysis rule, wherein the login equipment state comprises a normal state, a state to be verified and an abnormal state.
It should be noted that, the real-time login device information of each game account in the target game platform includes an ip address of the real-time login device and an MAC address of the real-time login device,
further, the preset game account login device state analysis rule is as follows:
if the ip address and the MAC address of the real-time login device of a certain game account in the target game platform are respectively matched with the ip address and the MAC address of a certain frequently-logged-in device of a corresponding game account within a preset time period, recording the login device state of the game account as a normal state;
if the ip address or the MAC address of the real-time login equipment of a certain game account in the target game platform is matched with the ip address or the MAC address of certain frequently-logged-in equipment of a corresponding game account within a preset time period, recording the login equipment state of the game account as a state to be verified;
and if the ip address and the MAC address of the real-time login equipment of a certain game account in the target game platform are not matched with the ip address and the MAC address of each frequently-logged-in equipment of the corresponding game account within a preset time period, recording the login equipment state of the game account as an abnormal state.
And the game account login equipment state processing module is used for carrying out corresponding processing according to the login equipment state of each game account in the target game platform, screening each game account successfully logged in the target game platform and recording the game account successfully logged in as each appointed game account.
As a preferred scheme, the game account login device state processing module performs corresponding processing according to the login device state of each game account in the target game platform, and the specific processing mode is as follows:
according to the login equipment state of each game account in the target game platform, if the login equipment state of a certain game account in the target game platform is a normal state, allowing the login request of the game account; if the login equipment state of a certain game account in the target game platform is a to-be-verified state, notifying an operation user corresponding to the game account to perform number main real-name verification, and allowing the login request of the game account after the number main real-name verification is correct; if the login equipment state of a certain game account in the target game platform is in an abnormal state, informing a game account corresponding number owner to carry out auditing treatment, allowing the login request of the game account after the game account corresponding number owner passes the auditing treatment, and otherwise pulling the real-time login equipment information of the game account into a platform blacklist.
The game platform database is used for storing a user habit login time range and an average online time of a user single-time login game corresponding to each game account in a preset time period, storing an average operation time, an average game task operation score, an average game activity participation degree and an average game activity completion degree of the user single-time login game corresponding to each game account in the preset time period, and storing a standard market transaction amount corresponding to each game device.
In the embodiment, the real-time login equipment information of each game account in the target game platform and the frequent login equipment information in the preset time period are acquired, the login equipment states of each game account in the target game platform are contrastingly analyzed, and corresponding processing is performed according to the login equipment states of each game account in the target game platform, so that the resource stealing behavior of lawbreakers logging in the game accounts through strange equipment is avoided, the login safety of the game accounts of the game platform is further effectively ensured, the possibility of stealing the game accounts is reduced, the safety supervision level of the game platform on the game accounts of the users is further improved, and the development of the game platform in the later period is greatly promoted.
The user behavior parameter acquisition module: the method is used for acquiring user behavior parameters of each appointed game account in the target game platform, wherein the user behavior parameters comprise user login habit behavior parameters, user operation behavior parameters and user transaction behavior parameters.
As a preferred scheme, the user login habit behavior parameters comprise user login time and user online time; the user operation behavior parameters comprise user operation duration, game task operation scores, game activity participation and game activity completion; the user transaction behavior parameters comprise equipment transaction information and game currency transaction information, wherein the equipment transaction information comprises the number of various transaction equipment and the total equipment transaction amount, and the game currency transaction information comprises the game currency count and the game currency expenditure amount.
The user behavior parameter analysis module is used for analyzing and obtaining the user behavior parameters of the appointed game accounts in the target game platform according to the user behavior parameters of the appointed game accounts in the target game platform, wherein the user behavior parameters conform to the proportional coefficient.
As a preferred scheme, the user behavior parameter analysis module analyzes that the user behavior parameters of each specified game account in the target game platform conform to the proportional coefficient, and the specific analysis content includes:
according to the user habit login time range and the average online time of the single-time login game of the user corresponding to each game account in the preset time period stored in the game platform database, extracting the user habit login time range and the average online time of the single-time login game of the user corresponding to each specified game account in the preset time period, comparing the user login time of the user login habit behavior parameter of each specified game account in the target game platform with the user habit login time range of the specified game account in the preset time period to obtain the user login time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform, analyzing the user online time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform according to the user online time of the user login habit behavior parameter of each specified game account in the target game platform, marking the user login time conformity weight factor and the user online time conformity weight factor of the user login habit behavior parameters of each appointed game account in the target game platform as deltaia1And deltaia2Where i 1, 2.., n, i denotes the number of the i-th designated game account;
enabling the user login time in the user login habit behavior parameters of each appointed game account in the target game platform to accord with the weight factor deltaia1According with the user online time length as a weight factor deltaia2Substituting the user login habit behavior parameters into the formula xi for the analysis of the proportional coefficienti＝λ1*δia1+λ2*δia2Obtaining the user login habit line of each appointed game account number in the target game platformFor the parameter to conform to the scaling factor xiiWherein λ is1And λ2And respectively representing the preset user login time and the corresponding coincidence correction index of the user online time.
It should be noted that, in the above-mentioned user login habit behavior parameters of each specified game account in the target game platform, the comparison and obtaining manner that the user login time meets the weight factor is as follows:
if the user login time in the user login habit behavior parameter of a certain specified game account in the target game platform is within the corresponding user habit login time range of the specified game account in the preset time period, the user login time in the user login habit behavior parameter of the specified game account in the target game platform conforms to the weight factor of delta ', otherwise, the user login time in the user login habit behavior parameter of the specified game account in the target game platform conforms to the weight factor of delta', and the user login time in the user login habit behavior parameter of each specified game account in the target game platform is counted to conform to the weight factor of deltaia1Wherein δia1δ' or δ ".
It should be noted that, in the above-mentioned user login habit behavior parameters of each specified game account in the target game platform, the user online time length conforms to the weight factor analysis mode formula
Where μ is expressed as a preset on-line duration compensation index, Δ tAllow forExpressed as a preset user online time allowed error value, tiThe user online time is represented as the user login habit behavior parameter of the ith specified game account in the target game platform,
the average online time of the single-time login game of the corresponding user in the preset time period is represented as the ith specified game account.
As a preferred scheme, the analyzing module for the user behavior parameters analyzes that the user behavior parameters of each specified game account in the target game platform conform to the proportionality coefficient, and the specific analysis content further includes:
according to the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each game account stored in the game platform database, extracting the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each appointed game account, and respectively marking the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each appointed game account as
Analyzing the user operation behavior parameters of each appointed game account in the target game platform to accord with the proportional coefficient
Wherein
The user operation behavior parameter expressed as the ith appointed game account number in the target game platform conforms to a proportional coefficient sigma1、σ2、σ3Respectively expressed as corresponding correction indexes, delta p, of operation duration, task operation score and activity participation completion degree in preset user operation behaviorsAllow forb1、ΔpAllow forb3、ΔpAllow forb4Respectively expressed as the preset allowable error value of the operation time length of the user single-time login game, the allowable error value of the participation degree of the game activity, the allowable error value of the completion degree of the game activity, pib1、pib2、pib3、pib4Respectively representing the user operation duration and the game as the user operation behavior parameters of the ith specified game account number in the target game platformThe task operation score, the game activity participation degree and the game activity completion degree, and e is expressed as a natural constant.
As a preferred scheme, the analyzing module for the user behavior parameters analyzes that the user behavior parameters of each specified game account in the target game platform conform to the proportionality coefficient, and the specific analysis content further includes:
extracting standard market transaction amount corresponding to each game equipment stored in a game platform database, screening the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in a target game platform, and marking the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in the target game platform as ri jJ is 1,2, and m, j is the number of the jth transaction equipment;
analyzing to obtain user transaction behavior parameters of each appointed game account number in the target game platform according to equipment transaction information and game currency transaction information in the user transaction behavior parameters of each appointed game account number in the target game platform, wherein the user transaction behavior parameters conform to the proportional coefficient
It should be noted that, the user transaction behavior parameters of each designated game account in the target game platform conform to the proportional coefficient analysis formula as
η1And η2Are respectively expressed as coincidence correction indexes, R 'corresponding to preset equipment transaction information and game currency transaction information'iThe total amount of the equipment transaction, x, is represented in the user transaction behavior parameter of the ith specified game account number in the target game platformi jRespectively representing the number of jth transaction equipment in the user transaction behavior parameters of the ith specified game account number in the target game platform, delta RError ofExpressed as a preset gaming equipment transaction allowance amount, yi Preparation ofShowing the single game currency preset for the ith specified game account numberThreshold of money out, yi fThe f-th game currency expenditure amount in the user transaction behavior parameter of the ith designated game account number in the target game platform is represented, wherein f is 1,2iThe number of game currency payouts in the user transaction behavior parameter of the ith specified game account number in the target game platform is represented.
The game account comprehensive safety factor analysis module is used for analyzing the comprehensive safety factor of each game account in the target game platform according to the condition that the user behavior parameters of each appointed game account in the target game platform accord with the proportional coefficient, comparing the comprehensive safety factor with a preset standard safety factor threshold value respectively, and performing corresponding early warning processing according to the comparison analysis result.
As a preferred scheme, the comprehensive security coefficient analysis module analyzes the comprehensive security coefficient of each game account in the target game platform in a specific analysis mode:
matching the user login habit behavior parameters of each appointed game account number in the target game platform with the proportionality coefficient xiiThe user operation behavior parameters accord with the proportional coefficients
According with the user transaction behavior parameter
Substitution formula
Obtaining the comprehensive safety factor omega of each game account number in the target game platformiWherein x is1、χ2、χ3Respectively expressed as preset safety influence factors corresponding to user login habit behavior, user operation behavior and user transaction behavior, and x1+χ2+χ3＝1。
As a preferred scheme, the game account comprehensive safety coefficient analysis module performs corresponding early warning processing according to a comparison analysis result, and specifically includes:
the comprehensive safety factor of each game account in the target game platform is compared with a preset standard safety factor threshold, if the comprehensive safety factor of a certain game account in the target game platform is smaller than the preset standard safety factor threshold, the game account in the target game platform is in a number stealing state, a number stealing early warning prompt is sent to the target game platform, and after the target game platform receives the number stealing early warning prompt sent by the game account, a number owner corresponding to the game account is informed to carry out emergency processing.
In the embodiment, the invention obtains the user behavior parameters of each appointed game account in the target game platform by obtaining the user behavior parameters of each appointed game account in the target game platform, analyzes the comprehensive safety factor of each game account in the target game platform, compares the comprehensive safety factor with the preset standard safety factor threshold value, the corresponding early warning treatment is carried out according to the comparison and analysis result, thereby realizing the real-time supervision of the user behavior parameters after the game account is logged in, breaking the limitation of the existing game platform on the safety supervision of the game account, the problem that the abnormal operation behavior cannot be processed in time after part of game account numbers are stolen is avoided to the greatest extent, and then reduce the virtual property loss of the user that the game account corresponds to, ensure that the game user's experience of playing is not influenced, further avoid the user of game platform to run off.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. The utility model provides a game account number monitoring analysis early warning management system based on feature analysis which characterized in that includes:
a frequently-logged-in equipment information acquisition module: the system comprises a target game platform, a server and a server, wherein the target game platform is used for acquiring historical login equipment information of each game account in the target game platform within a preset time period, and obtaining frequent login equipment information of each game account in the target game platform within the preset time period through comparison;
the game account login equipment state analysis module: the system comprises a target game platform, a storage module and a control module, wherein the target game platform is used for acquiring real-time login equipment information of each game account in the target game platform and comparing and analyzing the login equipment state of each game account in the target game platform;
the game account login equipment state processing module comprises: the system is used for carrying out corresponding processing according to the login equipment state of each game account in the target game platform, screening each successfully logged game account in the target game platform and recording as each appointed game account;
game platform database: the system comprises a game device, a game system and a game system, wherein the game device is used for storing a user habit login time range and an average online time of a user single-time login game corresponding to each game account in a preset time period, simultaneously storing an average operation time, an average game task operation score, an average game activity participation degree and an average game activity completion degree of each game account in a user single-time login game corresponding to each preset time period, and storing standard market transaction amount corresponding to each game device;
the user behavior parameter acquisition module: the system comprises a target game platform, a user operation behavior parameter acquisition module, a game execution module and a game execution module, wherein the target game platform is used for acquiring user behavior parameters of each appointed game account, and the user behavior parameters comprise a user login habit behavior parameter, a user operation behavior parameter and a user transaction behavior parameter;
the user behavior parameter analysis module: the system comprises a target game platform, a game server and a game server, wherein the target game platform is used for acquiring user behavior parameters of each appointed game account in the target game platform according to the user behavior parameters of each appointed game account in the target game platform;
the game account comprehensive safety coefficient analysis module: and the comprehensive safety factor analysis module is used for analyzing the comprehensive safety factor of each game account in the target game platform according to the condition that the user behavior parameters of each appointed game account in the target game platform accord with the proportional coefficient, comparing the comprehensive safety factor with a preset standard safety factor threshold value respectively, and performing corresponding early warning processing according to the comparison and analysis result.
2. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, characterized in that: the corresponding specific acquisition mode in the frequently-logged-in equipment information acquisition module is as follows:
extracting information of each historical login device of each game account in a preset time period from a target game platform background, wherein each piece of historical login device information comprises an ip address of each historical login device and an MAC address of each historical login device, counting the historical login times of each ip address and the historical login times of each MAC address of each game account in the target game platform in the preset time period, recording the ip address as the ip address of the frequently-logged device of each game account in the preset time period if the historical login times of a certain ip address of each game account in the target game platform in the preset time period is larger than a preset threshold of the historical login times, and counting the ip address of each frequently-logged device of each game account in the target game platform in the preset time period; similarly, the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are counted, and the ip addresses and the MAC addresses of the respective frequently-logged devices of the game accounts in the target game platform within the preset time period are recorded as the information of the frequently-logged devices of the game accounts within the preset time period.
3. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the method for analyzing the state of the login equipment of each game account in the target game platform by comparing and analyzing the state of the login equipment of each game account in the game account login equipment state analysis module specifically comprises the following steps:
the method comprises the steps of obtaining real-time login equipment information of each game account in a target game platform, comparing the real-time login equipment information of each game account in the target game platform with the frequently-logged-in equipment information of the corresponding game account in a preset time period, and analyzing to obtain the login equipment state of each game account in the target game platform according to a preset game account login equipment state analysis rule, wherein the login equipment state comprises a normal state, a state to be verified and an abnormal state.
4. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the game account login equipment state processing module carries out corresponding processing according to the login equipment state of each game account in the target game platform, and the specific processing mode is as follows:
according to the login equipment state of each game account in the target game platform, if the login equipment state of a certain game account in the target game platform is a normal state, allowing the login request of the game account; if the login equipment state of a certain game account in the target game platform is a to-be-verified state, notifying an operation user corresponding to the game account to perform number main real-name verification, and allowing the login request of the game account after the number main real-name verification is correct; if the login equipment state of a certain game account in the target game platform is in an abnormal state, informing a game account corresponding number owner to carry out auditing treatment, allowing the login request of the game account after the game account corresponding number owner passes the auditing treatment, and otherwise pulling the real-time login equipment information of the game account into a platform blacklist.
5. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the user login habit behavior parameters comprise user login time and user online time; the user operation behavior parameters comprise user operation duration, game task operation scores, game activity participation and game activity completion; the user transaction behavior parameters comprise equipment transaction information and game currency transaction information, wherein the equipment transaction information comprises the number of various transaction equipment and the total equipment transaction amount, and the game currency transaction information comprises the game currency count and the game currency expenditure amount.
6. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the user behavior parameter analysis module analyzes that the user behavior parameters of each appointed game account in the target game platform accord with the proportional coefficient, and the specific analysis content comprises the following steps:
according to the user habit login time range and the average online time of the single-time login game of the user corresponding to each game account in the preset time period stored in the game platform database, extracting the user habit login time range and the average online time of the single-time login game of the user corresponding to each specified game account in the preset time period, comparing the user login time of the user login habit behavior parameter of each specified game account in the target game platform with the user habit login time range of the specified game account in the preset time period to obtain the user login time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform, analyzing the user online time coincidence weight factor of the user login habit behavior parameter of each specified game account in the target game platform according to the user online time of the user login habit behavior parameter of each specified game account in the target game platform, marking the user login time conformity weight factor and the user online time conformity weight factor of the user login habit behavior parameters of each appointed game account in the target game platform as deltaia1And deltaia2Where i 1, 2.., n, i denotes the number of the i-th designated game account;
enabling the user login time in the user login habit behavior parameters of each appointed game account in the target game platform to accord with the weight factor deltaia1According with the user online time length as a weight factor deltaia2Substituting the user login habit behavior parameters into the formula xi for the analysis of the proportional coefficienti＝λ1*δia1+λ2*δia2Obtaining user login habit behavior parameters of each appointed game account number in the target game platform according with the proportionality coefficient xiiWherein λ is1And λ2Respectively representing the preset user login time and the corresponding correction index of the user online time.
7. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the user behavior parameter analysis module analyzes that the user behavior parameters of each specified game account in the target game platform conform to the proportional coefficient, and the specific analysis content further comprises the following steps:
according to the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each game account stored in the game platform database, extracting the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each appointed game account, and respectively marking the average operation duration, the average game task operation score, the average game activity participation degree and the average game activity completion degree of the single-time login game of the corresponding user in the preset time period of each appointed game account as
Analyzing the user operation behavior parameters of each appointed game account in the target game platform to accord with the proportional coefficient
Wherein
The user operation behavior parameter expressed as the ith appointed game account number in the target game platform conforms to a proportional coefficient sigma1、σ2、σ3Respectively expressed as corresponding correction indexes, delta p, of operation duration, task operation score and activity participation completion degree in preset user operation behaviorsAllow forb1、ΔpAllow forb3、ΔpAllow forb4Respectively expressed as the preset allowable error value of the operation time length of the user single-time login game, the allowable error value of the participation degree of the game activity, the allowable error value of the completion degree of the game activity, pib1、pib2、pib3、pib4The game parameters are respectively expressed as the user operation duration, the game task operation score, the game activity participation degree and the game activity completion degree of the user operation behavior parameter of the ith appointed game account in the target game platform, and e is expressed as a natural constant.
8. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the user behavior parameter analysis module analyzes that the user behavior parameters of each appointed game account in the target game platform conform to the proportional coefficient, and the specific analysis content further comprises the following steps:
extracting standard market transaction amount corresponding to each game equipment stored in a game platform database, screening the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in a target game platform, and marking the standard market transaction amount corresponding to each transaction equipment in the user transaction behavior parameters of each appointed game account number in the target game platform as ri jJ is 1,2, and m, j is the number of the jth transaction equipment;
analyzing to obtain user transaction behavior parameters of each appointed game account number in the target game platform according to equipment transaction information and game currency transaction information in the user transaction behavior parameters of each appointed game account number in the target game platform, wherein the user transaction behavior parameters conform to the proportional coefficient
9. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the comprehensive security coefficient analysis module for the game account numbers analyzes the comprehensive security coefficient of each game account number in the target game platform, and the specific analysis mode is as follows:
matching the user login habit behavior parameters of each appointed game account number in the target game platform with the proportionality coefficient xiiThe user operation behavior parameters accord with the proportionality coefficient
In accordance with the user transaction behavior parameters
Substitution formula
Obtaining the comprehensive safety factor omega of each game account number in the target game platformiTherein x1、χ2、χ3Respectively expressed as preset safety influence factors corresponding to user login habit behavior, user operation behavior and user transaction behavior, and x1+χ2+χ3＝1。
10. The game account monitoring, analyzing and early warning management system based on feature analysis as claimed in claim 1, wherein: the game account comprehensive safety factor analysis module carries out corresponding early warning processing according to the comparison and analysis result, and the method specifically comprises the following steps:
the comprehensive safety factor of each game account in the target game platform is compared with a preset standard safety factor threshold, if the comprehensive safety factor of a certain game account in the target game platform is smaller than the preset standard safety factor threshold, the game account in the target game platform is in a number stealing state, a number stealing early warning prompt is sent to the target game platform, and after the target game platform receives the number stealing early warning prompt sent by the game account, a game account corresponding number owner is informed to carry out emergency processing.
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