CN116747528B - Game background user supervision method and system - Google Patents
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Abstract
The invention discloses a method and a system for supervising a game background user, which relate to the technical field of game background user supervision and comprise a data acquisition module, a hidden danger analysis module, a comparison module, a comprehensive analysis module and an early warning module; the data acquisition module acquires information of the game background user supervision system during operation, including transaction detection evaluation information and transaction processing performance information, and processes the transaction detection evaluation information and the transaction processing performance information after acquisition. According to the invention, through monitoring the abnormal hidden danger situation when the game background user supervision system runs, when the game background user supervision system has abnormal hidden danger, the early warning prompt is sent out in time to inform the manager of the abnormal hidden danger situation of the system, so that the intelligent perception of the abnormal hidden danger situation of the system is realized, the timeliness of the system for finding problems is improved, and the game background user supervision system is convenient for efficiently supervising the traffic of users.
Description
Technical Field
The invention relates to the technical field of game background user supervision, in particular to a game background user supervision method and system.
Background
A game background user administration system is a software system for monitoring, managing and maintaining game user behavior. Such systems are commonly used by game developers or operators to ensure fairness, security, stability of the game environment, and to protect player's interests, and game background user administration systems mainly monitor users' game behavior, chat and social behavior, transaction and economic activity behavior, plug-in and cheating behavior, and other abnormal activity behavior, etc.
The game background user supervision system supervises user transactions to maintain the healthy development of games and ensure the fairness of games and the rights and interests of users, and can detect and prevent fraudulent activities, plug-in programs and cheating activities, which possibly damage the balance and fairness of games and affect the game experience of other players, by supervising the user transactions. The supervisory system can identify bad players or illegal transaction behaviors, protect the interests of the players, and ensure that they can enjoy the game in a fair environment without being affected by unfair competition. The supervisory system can monitor the transaction behavior of the virtual currency, discover and prevent potential illegal behaviors in time, and an economic system in the game is often an important component of game balance. Through supervision of user transactions, phenomena such as inflation, abnormal fluctuation of article prices and the like can be avoided, and balance of game economy is maintained.
The prior art has the following defects: however, when the operation of the game background user supervision system has abnormal hidden trouble, the system cannot intelligently sense, the influence caused by the abnormal hidden trouble is larger and larger along with the time, and finally the system operation is caused to be failed, when the system fails, the system can find that serious hysteresis exists in the finding problem, so that the game background user supervision system is inconvenient to efficiently supervise the user's delivery, and secondly, when the game background user supervision system operation has abnormal hidden trouble and is not timely found, the damage degree of the game background user supervision system is further increased during the period, and the difficulty and cost of system fault maintenance are increased.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a method and a system for supervising a game background user, which are used for solving the problems in the background technology.
In order to achieve the above object, the present invention provides the following technical solutions: a game background user supervision system comprises a data acquisition module, a hidden danger analysis module, a comparison module, a comprehensive analysis module and an early warning module;
The data acquisition module acquires information of the game background user supervision system during operation, including transaction detection evaluation information and transaction processing performance information, and transmits the transaction detection evaluation information and the transaction processing performance information to the hidden danger analysis module after being acquired;
the hidden danger analysis module establishes a data analysis model with the processed transaction detection evaluation information and the transaction processing performance information in the operation process of the game background user supervision system, generates a hidden danger probability evaluation index, and transmits the hidden danger probability evaluation index to the comparison module;
the comparison module is used for comparing the hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal and transmitting the risk signal to the comprehensive analysis module;
and the comprehensive analysis module is used for establishing a data set for comprehensive analysis of a plurality of hidden danger probability evaluation indexes generated during subsequent running of the game background user supervision system after receiving the high risk signals generated during the running of the game background user supervision system, generating accidental signals or non-accidental signals, transmitting the signals to the early warning module, and sending or not sending early warning prompts through the early warning module.
Preferably, the transaction detection and evaluation information comprises comprehensive evaluation index abnormal hiding coefficients, and after the acquisition, the data acquisition module marks the comprehensive evaluation index abnormal hiding coefficients as，
The transaction processing performance information comprises a transaction request response time length abnormal hiding coefficient and a transaction throughput stabilizing coefficient, and after the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient are acquired, the data acquisition module respectively marks the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient asAnd->。
Preferably, the logic for comprehensively evaluating the acquisition of the index anomaly concealment coefficients is as follows:
s101, setting a preset reference value for a comprehensive evaluation index when a game background user supervision system runs, and calibrating the preset reference value for the comprehensive evaluation index as，/>Greater than 1;
the comprehensive evaluation index, namely the F1 value, with the value range between 0 and 1 is an index which comprehensively considers the matching accuracy and recall;
s102, acquiring comprehensive evaluation indexes of the game background user supervision system in different time periods within the T time, and calibrating the comprehensive evaluation indexes as，xA number representing the overall evaluation index of the game background user supervision system at different time periods during the T time,x=1、2、3、4、……、m，mis a positive integer;
the expression of the comprehensive evaluation index calculation is:in the formula, precision represents the matching accuracy, and the matching accuracy refers to the proportion of abnormal transactions in the supervision system judged to be abnormal transactions, and the calculation method is as follows: match accuracy = number of abnormal transactions correctly matched/number of all abnormal transactions determined, recall represents Recall, which refers to the ratio between the number of abnormal transactions correctly matched by the supervisory system and the number of all actual abnormal transactions, calculated by: recall = number of abnormal transactions correctly matched/number of all actual abnormal transactions;
S103, calculating an abnormal hiding coefficient of the comprehensive evaluation index, wherein the calculated expression is as follows:。
preferably, the logic for obtaining the transaction request response time abnormal concealment coefficients is as follows:
s201, acquiring an optimal transaction request response time length range when the game background user supervision system operates, and calibrating the optimal transaction request response time length range as；
S202, acquiring transaction request response time length when the game background user supervision system operates within T time, and calibrating the transaction request response time length as，yRepresenting gamesThe number of transaction request response durations when the background user supervision system is running within T time,y=1、2、3、4、……、n，nis a positive integer;
s203, the response time length range of the transaction request is smaller than the optimal response time length rangeThe response time of the transaction request between the two is marked as +.>，vRepresenting less than the optimal transaction request response duration range +.>The number of the transaction request response time length in between,v=1、2、3、4、……、N，Nis a positive integer;
s204, calculating abnormal hiding coefficients of response time length of the transaction request, wherein the calculated expression is as follows:。
preferably, the logic for transaction throughput stability factor acquisition is as follows:
s201, acquiring average transaction throughput of a game background user supervision system in different time periods within T time, and calibrating the average transaction throughput as ，hA number representing the average transaction throughput of the gaming background user regulatory system over different time periods during time T,h=1、2、3、4、……、q，qis a positive integer;
s202, calculating standard deviation of average transaction throughput of a game background user supervision system in different time periods within T time, and calibrating the standard deviation asLThen:wherein->Is a gameThe average transaction throughput of the game background user supervision system in different time periods within the time T is obtained according to the following calculation formula:
；
s203, calculating a transaction throughput stability coefficient, wherein the calculated expression is as follows:。
preferably, the hidden danger analysis module obtains the abnormal hiding coefficient of the comprehensive evaluation indexTransaction request response time abnormal conceal coefficient>Transaction throughput stability factor->Then, a data analysis model is built, and a hidden danger probability evaluation index is generated>The formula according to is: />In the formula->、/>、/>Respectively, comprehensive evaluation index anomaly conceal coefficient +.>Abnormal hiding coefficient of transaction request response time lengthTransaction throughput stability factor->Is a preset proportionality coefficient of>、/>、/>Are all greater than 0.
Preferably, the comparison module compares the hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold, if the hidden danger probability evaluation index is greater than or equal to the hidden danger probability evaluation index reference threshold, a high risk signal is generated through the comparison module and is transmitted to the comprehensive analysis module, and if the hidden danger probability evaluation index is smaller than the hidden danger probability evaluation index reference threshold, a low risk signal is generated through the comparison module and is transmitted to the comprehensive analysis module.
Preferably, after the comprehensive analysis module receives a high risk signal generated by the game background user supervision system during operation, a data set is established for hidden danger probability evaluation indexes generated by the game background user supervision system during subsequent operation, and the data set is calibrated asGThen
，/>，cIs a positive integer;
calculating the average value and standard deviation of a plurality of hidden danger probability evaluation indexes in the data set, and calibrating the average value and the standard deviation asQ1 andQ2, then:wherein->；
Average value of a plurality of hidden danger probability evaluation indexes in a data setQ1 and standard deviationQ2 respectively comparing the abnormal hidden danger situation with a preset hidden danger probability evaluation index reference threshold value and a preset standard deviation reference threshold value, and comprehensively analyzing the abnormal hidden danger situation of the game background user supervision system, wherein the analysis result is as follows:
if the average value of a plurality of hidden danger probability evaluation indexes in the data setQ1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is smaller than the standard deviation reference threshold, generating an accidental signal through the comprehensive analysis module, transmitting the signal to the early warning module, and not sending an early warning prompt through the early warning module;
if the average value of a plurality of hidden danger probability evaluation indexes in the data set Q1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is greater than or equal to the standard deviation reference threshold, or if the average value of a plurality of hidden danger probability evaluation indexes in the data setQAnd if the potential risk probability evaluation index reference threshold value is greater than or equal to 1, generating a non-accidental signal through the comprehensive analysis module, transmitting the signal to the early warning module, and sending an early warning prompt through the early warning module.
A game background user supervision method comprises the following steps:
collecting information of a game background user supervision system during operation, wherein the information comprises transaction detection evaluation information and transaction processing performance information, and processing the transaction detection evaluation information and the transaction processing performance information after collecting the information;
establishing a data analysis model of the transaction detection evaluation information and the transaction processing performance information which are processed in the operation process of the game background user supervision system, and generating a hidden danger probability evaluation index;
comparing a hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal;
after a high-risk signal is generated when the game background user supervision system operates, a data set is built for comprehensively analyzing a plurality of hidden danger probability evaluation indexes generated when the game background user supervision system operates later, an accidental signal or a non-accidental signal is generated, and an early warning prompt is sent or not sent to the signal.
In the technical scheme, the application has the technical effects and advantages that:
according to the application, through monitoring the abnormal hidden trouble condition of the game background user supervision system during operation, when the game background user supervision system has abnormal hidden trouble, early warning prompt is sent out in time to inform management personnel of the abnormal hidden trouble condition of the system, so that intelligent perception of the abnormal hidden trouble condition of the system is realized, timeliness of the system discovery problem is improved, the game background user supervision system is convenient for efficiently supervising the delivery and the implementation of users, and meanwhile, the damage degree of the game background user supervision system is reduced, so that the difficulty and the cost of system fault maintenance are reduced;
according to the application, through comprehensively analyzing and judging the abnormal hidden danger situation when the game background user monitors the system to operate, the situation that the accidental abnormal hidden danger is sent out to give out the early warning prompt can be effectively prevented, the trust degree of the manager on the early warning prompt of the system is improved, the manager can efficiently monitor the system, and meanwhile, the system can stably and efficiently operate.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for those skilled in the art.
FIG. 1 is a schematic diagram of a method and system for monitoring a background user of a game according to the present invention.
FIG. 2 is a flow chart of a method and system for monitoring a background user of a game according to the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.
The invention provides a game background user supervision system shown in figure 1, which comprises a data acquisition module, a hidden danger analysis module, a comparison module, a comprehensive analysis module and an early warning module;
the data acquisition module acquires information of the game background user supervision system during operation, including transaction detection evaluation information and transaction processing performance information, and transmits the transaction detection evaluation information and the transaction processing performance information to the hidden danger analysis module after being acquired;
the transaction detection evaluation information comprises a comprehensive evaluation index abnormal hiding coefficient, and after the acquisition, the data acquisition module marks the comprehensive evaluation index abnormal hiding coefficient as ；
When the comprehensive evaluation index (i.e. the F1 value, the F1 value is an index comprehensively considering the matching accuracy and recall rate, and is used for measuring the matching capability of the supervision system to abnormal transactions) of the transaction of the background user by the game background user supervision system is low, the following serious effects are caused to the transaction of the background user:
the risk of false sealing and sealing forbidden increases: the lower comprehensive evaluation index means that the supervision system is poor in matching accuracy and recall rate, namely the system is easy to misjudge that normal transaction is abnormal transaction (high false alarm rate) and is easy to miss real abnormal transaction (low recall rate), which can cause the supervision system to misseal the transaction of a normal user or miss the real illegal behavior, and increase the sealing risk for a background user;
restrictions on normal transactions: a supervisory system with a low comprehensive evaluation index may excessively limit and interfere with normal transactions of the background user, such as limiting transaction frequency, transaction amount, or transaction objects, which may affect transaction flexibility and experience of the background user;
background user complaints increase: background users may be discontented because transactions are misjudged as abnormal or are improperly limited, so that complaints are increased, and reputation of game operators and user satisfaction are affected;
Adverse effects on game economy: the low-accuracy supervision system may not be capable of effectively monitoring and preventing illegal transactions and fraudulent activities, so that economy in the game is unstable, price fluctuation of articles is large, and balance and fairness of the game are affected;
and (3) supervision cost increases: the low comprehensive evaluation index means that the supervision system needs more manual intervention and investigation to handle the situations of false alarm and missing alarm, so that the supervision cost is increased;
therefore, the comprehensive evaluation index during the operation of the game background user supervision system is monitored, and the situation that the comprehensive evaluation index has abnormal hidden trouble can be perceived in time;
the logic for comprehensively evaluating the acquisition of the index anomaly concealment coefficients is as follows:
s101, setting a preset reference value for a comprehensive evaluation index when a game background user supervision system runs, and calibrating the preset reference value for the comprehensive evaluation index as，/>Greater than 1;
it should be noted that, the preset reference value of the comprehensive evaluation index is a quantized specific reference value, which is not specifically limited herein, is a value greater than 1, and the comprehensive evaluation index, that is, the F1 value, has a value ranging from 0 to 1, is an index comprehensively considering the matching accuracy (Precision) and the Recall (Recall), and is used for measuring the matching capability of the supervision system to the abnormal transaction, and a high F1 value means that the supervision system can accurately identify the abnormal transaction, avoid misjudging the normal transaction as the abnormal transaction, and is helpful for ensuring that the supervision system can more accurately detect and process the illegal transaction, improving the supervision effect, and a high F1 value means that the supervision system has higher Recall of the abnormal transaction, can effectively reduce the miss report, find and process the real abnormal transaction as much as possible, and ensure the fairness of the game and the rights of users;
S102, acquiring comprehensive evaluation indexes of the game background user supervision system in different time periods (the time in the time periods is equal) in the T time, and calibrating the comprehensive evaluation indexes as，xA number representing the overall evaluation index of the game background user supervision system at different time periods during the T time,x=1、2、3、4、……、m，mis a positive integer;
the expression of the comprehensive evaluation index calculation is:in the formula, precision represents the matching accuracy, and the matching accuracy refers to the proportion of abnormal transactions in the supervision system judged to be abnormal transactions, and the calculation method is as follows: match accuracy = number of abnormal transactions correctly matched/number of all abnormal transactions determined, recall represents Recall, which refers to the ratio between the number of abnormal transactions correctly matched by the supervisory system and the number of all actual abnormal transactions, calculated by: recall = number of abnormal transactions correctly matched/number of all actual abnormal transactions;
it should be noted that, the number of abnormal transactions that are correctly matched refers to the number of abnormal transactions that are correctly identified and matched by the supervisory system, and in general, the supervisory system marks the detected abnormal transactions or puts the detected abnormal transactions into a database of abnormal transaction records, and the number of abnormal transactions that are correctly matched can be obtained by querying the number of abnormal transaction records;
The number of the abnormal transactions is the number of the abnormal transactions which are judged by the supervision system in a certain time range, wherein the supervision system generally marks the abnormal transactions in a classified manner or records the abnormal judgment condition of the transactions in a log, and the abnormal judgment condition can be obtained by counting the number of the abnormal transactions marked as abnormal;
the number of all actual abnormal transactions refers to the number of all abnormal transactions existing under the actual condition, and as the actual abnormal transactions may be caused by fraud, cheating or other illegal actions, the supervision system needs to interact with the game server or the database to acquire the number of the actual abnormal transactions;
s103, calculating an abnormal hiding coefficient of the comprehensive evaluation index, wherein the calculated expression is as follows:；
the calculation expression of the comprehensive evaluation index abnormal hidden coefficient shows that the larger the expression value of the comprehensive evaluation index abnormal hidden coefficient generated when the game background user supervision system operates in the T time is, the larger the probability of occurrence of abnormal hidden danger of the system is, and the smaller the expression value of the comprehensive evaluation index abnormal hidden coefficient generated when the game background user supervision system operates in the T time is, the smaller the probability of occurrence of abnormal hidden danger of the system is;
The transaction processing performance information comprises a transaction request response time length abnormal hiding coefficient and a transaction throughput stabilizing coefficient, and after the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient are acquired, the data acquisition module respectively marks the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient asAnd->；
When the game background user supervision system monitors the transaction of the background user, the longer transaction request response time of the background user transaction will cause the following serious influence on the background user transaction:
transaction reliability decreases: the long response time of the transaction request may cause the condition that the transaction request is overtime or fails in the processing process to increase, which reduces the reliability of the transaction, so that some transactions may not be successfully executed, thereby affecting the transaction quality of background users;
transaction instantaneity decreases: the long response time of the transaction request can lead a background user to wait for a long time when carrying out the transaction, so that the real-time performance of the transaction is reduced, which can influence certain transactions which need to be completed in time, in particular to the situations of virtual articles, game assets or competitive transactions and the like;
the transaction experience is poor: the long response time of the transaction request can cause the background user to feel uncomfortable and unsatisfactory, the transaction experience is poor, the user can be dissatisfied due to slow transaction processing, and even the transaction can be lost or no longer carried out;
Transaction activity is limited: to reduce the response time, the supervisory system may take limiting measures, such as limiting the transaction frequency or the transaction amount of the background user, and such limitations may affect the transaction freedom and flexibility of the background user, and reduce the quality of the transaction;
transaction backlog and delay: the long transaction request response time can cause the transaction request to be queued for processing in the monitoring system, thereby generating transaction backlog and delay, which can influence the timely completion of the transaction and can cause the background user transaction to be unable to be timely executed;
therefore, the transaction request response time length when the game background user supervision system operates is monitored, and the situation that the transaction request response time length has abnormal hidden trouble can be timely perceived;
the logic for acquiring the transaction request response time abnormal hiding coefficient is as follows:
s201, acquiring an optimal transaction request response time length range when the game background user supervision system operates, and calibrating the optimal transaction request response time length range as；
It should be noted that, the response time length of the transaction request under different load conditions can be evaluated by performing performance test and pressure test on the supervision system, and the response condition of the system is observed by simulating a large number of concurrent transaction requests and actual supervision scenes, so as to obtain the optimal response time length range of the transaction request under different loads of the system;
S202, acquiring transaction request response time length when the game background user supervision system operates within T time, and calibrating the transaction request response time length as，yA number representing the transaction request response duration when the gaming background user administration system is running within T time,y=1、2、3、4、……、n，nis a positive integer;
it should be noted that, the performance monitoring tool is used to monitor the running state of the supervisory system, including the response time of the transaction request, and can provide real-time performance indexes, such as promethaus, which is an open-source monitoring and alarming tool, and support multiple data models and query languages, and is used to monitor the performance indexes of the supervisory system in real time, including the response time of the transaction request;
s203, the response time length range of the transaction request is smaller than the optimal response time length rangeThe response time of the transaction request between the two is marked as +.>，vRepresenting less than the optimal transaction request response duration range +.>The number of the transaction request response time length in between,v=1、2、3、4、……、N，Nis a positive integer;
s204, calculating abnormal hiding coefficients of response time length of the transaction request, wherein the calculated expression is as follows:；
the calculation expression of the transaction request response time abnormal hidden coefficient shows that the larger the appearance value of the transaction request response time abnormal hidden coefficient generated when the game background user supervision system operates within the T time is, the larger the probability of occurrence of abnormal hidden danger of the system is, and the smaller the appearance value of the transaction request response time abnormal hidden coefficient generated when the game background user supervision system operates within the T time is, the smaller the probability of occurrence of abnormal hidden danger of the system is;
When the game background user supervision system monitors the transaction of the background user, if the transaction throughput stability of the transaction of the background user is poor, that is, the fluctuation of the transaction request quantity is large or cannot be stably maintained at a high level, the following serious influence is caused to the transaction of the background user:
delay and response time increase: unstable transaction throughput may result in increased transaction processing time, the transaction may thus be delayed for execution, affecting the user's transaction experience, and increased delay and response time may lead to user dissatisfaction and even user churn;
transaction failure and loss: unstable transaction throughput increases the risk of transaction failure and loss, and if background user transactions frequently fail or are lost, users may lose trust and choose not to conduct transactions any more;
data inconsistency: fluctuations in transaction throughput may lead to problems of data inconsistency, such as the occurrence of repeated transactions or missing transaction records, which can present difficulties in the supervision and data analysis of background user transactions;
system crashes and instabilities: if the transaction throughput fluctuates greatly, the system may bear excessive load, resulting in system breakdown or instability, which may lead to increased downtime, affecting the usability of the gaming service;
Security vulnerabilities: transaction throughput instability may give hackers or malicious users the opportunity to exploit security vulnerabilities, which they may attack when the exploitation system is overloaded, resulting in greater losses;
difficult to predict and plan: instability of transaction throughput makes it difficult for a background user supervisory system to predict and plan transaction processing capacity, which may lead to unreasonable allocation of resources, failing to efficiently meet transaction demands;
therefore, the transaction throughput of the game background user monitoring system during operation is monitored, and the situation that the transaction throughput has abnormal hidden trouble can be perceived in time;
the logic for transaction throughput stability factor acquisition is as follows:
s201, acquiring average transaction throughput of the game background user supervision system in different time periods (the time in the time period can be equal or unequal) within T time, and calibrating the average transaction throughput as，hA number representing the average transaction throughput of the gaming background user regulatory system over different time periods during time T,h=1、2、3、4、……、q，qis a positive integer;
it should be noted that, the game background user supervision system may record the time stamp and related information of each transaction into log files, and by analyzing these log files, the number of transactions completed in a specific time period may be calculated, so as to obtain an average transaction throughput;
S202, calculating standard deviation of average transaction throughput of a game background user supervision system in different time periods within T time, and calibrating the standard deviation asLThen:
wherein->For the average value of the average transaction throughput of the game background user supervision system in different time periods within the T time, the acquired calculation formula is as follows:
；
from standard deviationLAs can be seen, the gaming background user supervisor system has standard deviations of the average transaction throughput for different time periods during the T timeLThe larger the expression value of (2) is, the higher the expression value of (3) is, the game background user supervision system is in the T timeThe worse the stability of the transaction throughput of the game background user supervision system is, the better the stability of the transaction throughput of the game background user supervision system is in the T time is;
s203, calculating a transaction throughput stability coefficient, wherein the calculated expression is as follows:；
the calculation expression of the transaction throughput stability coefficient shows that the larger the expression value of the transaction throughput stability coefficient generated when the game background user supervision system operates in the T time is, the larger the probability of occurrence of abnormal hidden danger of the system is, and the smaller the expression value of the transaction throughput stability coefficient generated when the game background user supervision system operates in the T time is, the smaller the probability of occurrence of abnormal hidden danger of the system is;
The hidden danger analysis module establishes a data analysis model with the processed transaction detection evaluation information and the transaction processing performance information in the operation process of the game background user supervision system, generates a hidden danger probability evaluation index, and transmits the hidden danger probability evaluation index to the comparison module;
the hidden danger analysis module obtains the abnormal hidden coefficient of the comprehensive evaluation indexTransaction request response time abnormal conceal coefficient>Transaction throughput stability factor->Then, a data analysis model is established to generate hidden danger probability evaluation indexesThe formula according to is: />In the formula->、、/>Respectively, comprehensive evaluation index anomaly conceal coefficient +.>Transaction request response time abnormal conceal coefficient>Transaction throughput stability factor->Is a preset proportionality coefficient of>、/>、/>Are all greater than 0;
as can be seen from the calculation formula, the larger the comprehensive evaluation index abnormal hiding coefficient generated when the game background user supervision system operates within the T time is, the larger the transaction request response time abnormal hiding coefficient is, the larger the transaction throughput stability coefficient is, namely the hidden danger probability evaluation index isThe larger the appearance value of the system is, the larger the probability of occurrence of abnormal hidden danger of the system is, the smaller the abnormal hidden coefficient of the comprehensive evaluation index generated when the game background user supervision system operates within the T time is, the smaller the abnormal hidden coefficient of the transaction request response time length is, and the smaller the transaction throughput stability coefficient is, namely the hidden danger probability evaluation index +. >The smaller the appearance value of the (B) is, the smaller the probability of occurrence of abnormal hidden danger of the system is;
the comparison module is used for comparing the hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal and transmitting the risk signal to the comprehensive analysis module;
the comparison module compares the hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold, if the hidden danger probability evaluation index is larger than or equal to the hidden danger probability evaluation index reference threshold, a high risk signal is generated through the comparison module and transmitted to the comprehensive analysis module, and if the hidden danger probability evaluation index is smaller than the hidden danger probability evaluation index reference threshold, a low risk signal is generated through the comparison module and transmitted to the comprehensive analysis module;
the comprehensive analysis module is used for establishing a data set for comprehensive analysis on a plurality of hidden danger probability evaluation indexes generated during subsequent running of the game background user supervision system after receiving a high risk signal generated during the running of the game background user supervision system, generating an accidental signal or a non-accidental signal, transmitting the signal to the early warning module, and sending or not sending an early warning prompt through the early warning module;
After the comprehensive analysis module receives a high risk signal generated during the running of the game background user supervision system, a data set is established for hidden danger probability evaluation indexes generated during the subsequent running of the game background user supervision system, and the data set is calibrated asGThen，/>，cIs a positive integer;
calculating the average value and standard deviation of a plurality of hidden danger probability evaluation indexes in the data set, and calibrating the average value and the standard deviation asQ1 andQ2, then:
wherein, the liquid crystal display device comprises a liquid crystal display device,；
average value of a plurality of hidden danger probability evaluation indexes in a data setQ1 and standard deviationQ2 respectively comparing the abnormal hidden danger situation with a preset hidden danger probability evaluation index reference threshold value and a preset standard deviation reference threshold value, and comprehensively analyzing the abnormal hidden danger situation of the game background user supervision system, wherein the analysis result is as follows:
if the average value of a plurality of hidden danger probability evaluation indexes in the data setQ1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is smaller than the standard deviation reference threshold, generating an accidental signal through the comprehensive analysis module, transmitting the signal to the early warning module, and not sending an early warning prompt through the early warning module;
it should be noted that, when an average value of several hidden danger probability evaluation indexes in the data set appears Q1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is smaller than the standard deviation reference threshold, the situation that the hidden danger probability evaluation index in the data set is larger than or equal to the hidden danger probability evaluation index reference threshold is shown as an accidental situation;
if the average value of a plurality of hidden danger probability evaluation indexes in the data setQ1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is greater than or equal to the standard deviation reference threshold, or if the average value of a plurality of hidden danger probability evaluation indexes in the data setQ1 is larger than or equal to a hidden danger probability evaluation index reference threshold value, generating a non-accidental signal through a comprehensive analysis module, transmitting the signal to an early warning module, and sending an early warning prompt through the early warning module to prompt a manager system of a game background user supervision system to have abnormal hidden danger, so that intelligent perception of the abnormal hidden danger condition of the system is realized, timeliness of system discovery problems is improved, the game background user supervision system is convenient for efficiently supervising the traffic of users, and meanwhile, the damage degree of the game background user supervision system is reduced, so that the difficulty and cost of system fault maintenance are reduced;
if the number of occurrences is Average value of multiple hidden danger probability evaluation indexes in a setQ1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is greater than or equal to a standard deviation reference threshold, or the average value of a plurality of hidden danger probability evaluation indexes in a data setQWhen 1 is greater than or equal to the hidden danger probability evaluation index reference threshold, indicating that the hidden danger probability evaluation index in the data set is greater than or equal to the hidden danger probability evaluation index reference threshold, and the situation is not accidental;
according to the invention, through monitoring the abnormal hidden trouble condition of the game background user supervision system during operation, when the game background user supervision system has abnormal hidden trouble, early warning prompt is sent out in time to inform management personnel of the abnormal hidden trouble condition of the system, so that intelligent perception of the abnormal hidden trouble condition of the system is realized, timeliness of the system discovery problem is improved, the game background user supervision system is convenient for efficiently supervising the delivery and the implementation of users, and meanwhile, the damage degree of the game background user supervision system is reduced, so that the difficulty and the cost of system fault maintenance are reduced;
according to the invention, through comprehensively analyzing and judging the abnormal hidden danger situation when the game background user monitors the system to operate, the situation that the accidental abnormal hidden danger is sent out to give out the early warning prompt can be effectively prevented, the trust degree of the manager on the early warning prompt of the system is improved, the manager can efficiently monitor the system, and meanwhile, the system can stably and efficiently operate.
The invention provides a game background user supervision method as shown in fig. 2, which comprises the following steps:
collecting information of a game background user supervision system during operation, wherein the information comprises transaction detection evaluation information and transaction processing performance information, and processing the transaction detection evaluation information and the transaction processing performance information after collecting the information;
establishing a data analysis model of the transaction detection evaluation information and the transaction processing performance information which are processed in the operation process of the game background user supervision system, and generating a hidden danger probability evaluation index;
comparing a hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal;
after a high-risk signal is generated when the game background user supervision system operates, a data set is established for comprehensively analyzing a plurality of hidden danger probability evaluation indexes generated when the game background user supervision system operates later, an accidental signal or a non-accidental signal is generated, and an early warning prompt is sent or not sent to the signal;
the method for supervising the game background user provided by the embodiment of the invention is realized through the above-mentioned game background user supervising system, and the details of the method and the flow of the game background user supervising method are shown in the above-mentioned embodiment of the game background user supervising system, and are not repeated here.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the several embodiments provided by the present application, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
While certain exemplary embodiments of the present application have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the application. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the application, which is defined by the appended claims.
Claims (4)
1. The game background user supervision system is characterized by comprising a data acquisition module, a hidden danger analysis module, a comparison module, a comprehensive analysis module and an early warning module;
the data acquisition module acquires information of the game background user supervision system during operation, including transaction detection evaluation information and transaction processing performance information, and transmits the transaction detection evaluation information and the transaction processing performance information to the hidden danger analysis module after being acquired;
The transaction detection evaluation information comprises a comprehensive evaluation index abnormal hiding coefficient, and after the acquisition, the data acquisition module marks the comprehensive evaluation index abnormal hiding coefficient asThe transaction processing performance information comprises a transaction request response time length abnormal hiding coefficient and a transaction throughput stabilizing coefficient, and after the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient are acquired, the data acquisition module respectively marks the transaction request response time length abnormal hiding coefficient and the transaction throughput stabilizing coefficient as +.>And->；
The logic for comprehensively evaluating the acquisition of the index anomaly concealment coefficients is as follows:
s101, setting a preset reference value for a comprehensive evaluation index when a game background user supervision system runs, and calibrating the preset reference value for the comprehensive evaluation index as，/>Greater than 1;
the comprehensive evaluation index, namely the F1 value, with the value range between 0 and 1 is an index which comprehensively considers the matching accuracy and recall;
s102, acquiring comprehensive evaluation indexes of the game background user supervision system in different time periods within the T time, and marking the comprehensive evaluation indexesIs defined as，xA number representing the overall evaluation index of the game background user supervision system at different time periods during the T time,x=1、2、3、4、……、m，mis a positive integer;
the expression of the comprehensive evaluation index calculation is:in the formula, precision represents the matching accuracy, and the matching accuracy refers to the proportion of abnormal transactions in the supervision system judged to be abnormal transactions, and the calculation method is as follows: match accuracy = number of abnormal transactions correctly matched/number of all abnormal transactions determined, recall represents Recall, which refers to the ratio between the number of abnormal transactions correctly matched by the supervisory system and the number of all actual abnormal transactions, calculated by: recall = number of abnormal transactions correctly matched/number of all actual abnormal transactions;
S103, calculating an abnormal hiding coefficient of the comprehensive evaluation index, wherein the calculated expression is as follows:；
the logic for acquiring the transaction request response time abnormal hiding coefficient is as follows:
s201, acquiring an optimal transaction request response time length range when the game background user supervision system operates, and calibrating the optimal transaction request response time length range as；
S202, acquiring transaction request response time length when the game background user supervision system operates within T time, and calibrating the transaction request response time length as，yNumber representing transaction request response duration of game background user supervision system running in T time，y=1、2、3、4、……、n，nIs a positive integer;
s203, the response time length range of the transaction request is smaller than the optimal response time length rangeThe response time of the transaction request between the two is marked as +.>，vRepresenting less than the optimal transaction request response duration range +.>The number of the transaction request response time length in between,v=1、2、3、4、……、N，Nis a positive integer;
s204, calculating abnormal hiding coefficients of response time length of the transaction request, wherein the calculated expression is as follows:；
the logic for transaction throughput stability factor acquisition is as follows:
s201, acquiring average transaction throughput of a game background user supervision system in different time periods within T time, and calibrating the average transaction throughput as，hA number representing the average transaction throughput of the gaming background user regulatory system over different time periods during time T, h=1、2、3、4、……、q，qIs a positive integer;
s202, calculating standard deviation of average transaction throughput of a game background user supervision system in different time periods within T time, and calibrating the standard deviation asLThen:
wherein->For the average value of the average transaction throughput of the game background user supervision system in different time periods within the T time, the acquired calculation formula is as follows: />；
S203, calculating a transaction throughput stability coefficient, wherein the calculated expression is as follows:；
the hidden danger analysis module establishes a data analysis model with the processed transaction detection evaluation information and the transaction processing performance information in the operation process of the game background user supervision system, generates a hidden danger probability evaluation index, and transmits the hidden danger probability evaluation index to the comparison module;
the hidden danger analysis module obtains the abnormal hidden coefficient of the comprehensive evaluation indexTransaction request response time abnormal conceal coefficient>Transaction throughput stability factor->Then, a data analysis model is built, and a hidden danger probability evaluation index is generated>The formula according to is:
wherein->、/>、/>Respectively, comprehensive evaluation index anomaly conceal coefficient +.>Transaction request response time abnormal conceal coefficient>Transaction throughput stability factor->Is a preset proportionality coefficient of >、/>、/>Are all greater than 0;
the comparison module is used for comparing the hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal and transmitting the risk signal to the comprehensive analysis module;
and the comprehensive analysis module is used for establishing a data set for comprehensive analysis of a plurality of hidden danger probability evaluation indexes generated during subsequent running of the game background user supervision system after receiving the high risk signals generated during the running of the game background user supervision system, generating accidental signals or non-accidental signals, transmitting the signals to the early warning module, and sending or not sending early warning prompts through the early warning module.
2. The game background user supervision system according to claim 1, wherein the comparison module compares a hidden danger probability evaluation index generated when the game background user supervision system is running with a preset hidden danger probability evaluation index reference threshold, generates a high risk signal through the comparison module if the hidden danger probability evaluation index is greater than or equal to the hidden danger probability evaluation index reference threshold, and transmits the signal to the comprehensive analysis module, and generates a low risk signal through the comparison module if the hidden danger probability evaluation index is less than the hidden danger probability evaluation index reference threshold, and transmits the signal to the comprehensive analysis module.
3. The system of claim 2, wherein the analysis-by-synthesis module establishes a data set for a risk assessment index generated during subsequent operation of the system and calibrates the data set to beGThen，/>，cIs a positive integer;
calculating the average value and standard deviation of a plurality of hidden danger probability evaluation indexes in the data set, and calibrating the average value and the standard deviation asQ1 andQ2, then:wherein (1)>；
Average value of a plurality of hidden danger probability evaluation indexes in a data setQ1 and standard deviationQ2 respectively comparing the abnormal hidden danger situation with a preset hidden danger probability evaluation index reference threshold value and a preset standard deviation reference threshold value, and comprehensively analyzing the abnormal hidden danger situation of the game background user supervision system, wherein the analysis result is as follows:
if a plurality of hidden danger probability evaluation indexes in the data setAverage value of (2)Q1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is smaller than the standard deviation reference threshold, generating an accidental signal through the comprehensive analysis module, transmitting the signal to the early warning module, and not sending an early warning prompt through the early warning module;
If the average value of a plurality of hidden danger probability evaluation indexes in the data setQ1 is smaller than the hidden danger probability evaluation index reference threshold and the standard deviationQ2 is greater than or equal to the standard deviation reference threshold, or if the average value of a plurality of hidden danger probability evaluation indexes in the data setQAnd if the potential risk probability evaluation index reference threshold value is greater than or equal to 1, generating a non-accidental signal through the comprehensive analysis module, transmitting the signal to the early warning module, and sending an early warning prompt through the early warning module.
4. A method of gaming background user supervision implemented by a gaming background user supervision system according to any one of claims 1-3, comprising the steps of:
collecting information of a game background user supervision system during operation, wherein the information comprises transaction detection evaluation information and transaction processing performance information, and processing the transaction detection evaluation information and the transaction processing performance information after collecting the information;
establishing a data analysis model of the transaction detection evaluation information and the transaction processing performance information which are processed in the operation process of the game background user supervision system, and generating a hidden danger probability evaluation index;
comparing a hidden danger probability evaluation index generated when the game background user supervision system operates with a preset hidden danger probability evaluation index reference threshold value to generate a high-risk signal or a low-risk signal;
After a high-risk signal is generated when the game background user supervision system operates, a data set is built for comprehensively analyzing a plurality of hidden danger probability evaluation indexes generated when the game background user supervision system operates later, an accidental signal or a non-accidental signal is generated, and an early warning prompt is sent or not sent to the signal.
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