CN111488625A

CN111488625A - Data processing method and device

Info

Publication number: CN111488625A
Application number: CN202010238201.0A
Authority: CN
Inventors: 朱威果; 曾冠东; 王俊
Original assignee: Guangzhou Kugou Computer Technology Co Ltd
Current assignee: Guangzhou Kugou Computer Technology Co Ltd
Priority date: 2020-03-30
Filing date: 2020-03-30
Publication date: 2020-08-04
Anticipated expiration: 2040-03-30
Also published as: CN111488625B

Abstract

The application relates to a data processing method and device, and belongs to the field of communication. The method comprises the following steps: acquiring configuration information of a probability service in a target time period, wherein the configuration information comprises a theoretical probability corresponding to the probability service, a consumption amount required for purchasing the probability service and an output value of a service provided by the probability service, and the probability service runs in a service server; acquiring a consumption log and a service log of the probabilistic service in the target time period, wherein the consumption log is used for recording the condition that a user purchases the probabilistic service in the service server, and the service log is used for recording the condition that the service server provides the service for the user; and detecting whether the probabilistic service is tampered according to the consumption log and the service log of the probabilistic service in the target time period according to the configuration information. The method and the device can improve the safety of the probability service.

Description

Data processing method and device

Technical Field

The present application relates to the field of communications, and in particular, to a method and an apparatus for data processing.

Background

At present, income of probability services greatly contributes to income of all live broadcast services, and business departments can perform reasonable audit on rules of the probability services before the probability services are on line.

Although the reasonability audit is carried out before online, at present, after the probability service is online, personnel may tamper the data of the probability service, and arbitrage is carried out by utilizing the probability service. Data of the existing probability service is often tampered and cannot be found in time, so that the security of the probability service is low.

Disclosure of Invention

The embodiment of the application provides a data processing method and device, so that the safety of probability service is improved. The technical scheme is as follows:

in one aspect, the present application provides a method of data processing, the method including:

acquiring configuration information of a probability service in a target time period, wherein the configuration information comprises a theoretical probability corresponding to the probability service, a consumption amount required for purchasing the probability service and an output value of a service provided by the probability service, and the probability service runs in a service server;

acquiring a consumption log and a service log of the probabilistic service in the target time period, wherein the consumption log is used for recording the condition that a user purchases the probabilistic service in the service server, and the service log is used for recording the condition that the service server provides the service for the user;

and detecting whether the probabilistic service is tampered according to the consumption log and the service log of the probabilistic service in the target time period according to the configuration information.

Optionally, the detecting, according to the configuration information, whether the probabilistic service is tampered with in the consumption log and the service log of the probabilistic service in the target time period includes:

acquiring theoretical production proportion and theoretical probability of the probability service according to the configuration information;

acquiring the actual production proportion and the actual probability of the probability service according to the consumption log and the service log of the probability service in the target time period;

and detecting whether the probability service is tampered in the target time period according to the theoretical production proportion, the theoretical probability, the actual production proportion and the actual probability.

Optionally, the consumption log includes the consumption amount and the consumption time, and the service log includes the output value of the service and the providing time for providing the service;

the obtaining the actual production ratio of the probability service according to the consumption log and the service log of the probability service in the target time period comprises:

acquiring each consumption log of which the consumption time is within the target time period, and counting the consumption amount included in each consumption log within the target time period to obtain the total consumption amount;

obtaining each service log with the providing time in the target time period, and counting the output value of each service log in the target time period to obtain the total output value;

and calculating the ratio of the total output value to the total consumption amount to obtain the actual production proportion of the probability service in a target time period.

Optionally, the obtaining the actual probability of the probabilistic service according to the consumption log and the service log of the probabilistic service in the target time period includes:

counting the number of service logs in a target time period and counting the number of consumption logs in the target time period;

and calculating the ratio of the number of the service logs to the number of the consumption logs to obtain the actual probability of the probability service in a target time period.

Optionally, the detecting whether the probabilistic service is tampered in the target time period according to the theoretical production proportion, the theoretical probability, the actual production proportion, and the actual probability includes:

calculating a probability difference value between a theoretical probability and an actual probability of the probability service, and calculating a production ratio difference value between a theoretical production ratio and an actual production ratio of the probability service;

and under the condition that the probability difference value exceeds a probability threshold value and/or the production proportion difference value exceeds a production proportion threshold value, determining that the probability service is tampered in a target time period.

Optionally, after obtaining the consumption log and the service log of the probabilistic service in the target time period, the method further includes:

selecting a plurality of user accounts meeting preset conditions from the user accounts purchasing the probabilistic service in the target time period according to each consumption log and each service log in the target time period;

acquiring a device identifier corresponding to each user account in the plurality of user accounts to obtain a device identifier set, and counting the number of the user accounts corresponding to each device identifier in the device identifier set from the plurality of user accounts;

and selecting the equipment identifier of which the number of the user accounts exceeds a number threshold from the equipment identifier set, wherein the equipment corresponding to the selected equipment identifier is abnormal equipment.

Optionally, the consumption log includes the consumption amount, the consumption time, the user account and the device identifier corresponding to the user account, the service log includes the user account, the device identifier corresponding to the user account, the output value of the service and the providing time for providing the service,

selecting a plurality of user accounts meeting preset conditions from the user accounts purchasing the probabilistic service in the target time period according to each consumption log and each service log in the target time period, wherein the selecting comprises the following steps:

according to the consumption logs in the target time period, counting the total consumption amount corresponding to the user accounts purchasing the probabilistic service in the target time period, and acquiring a first number of user accounts with the maximum total consumption amount; and/or the presence of a gas in the gas,

according to the service logs in the target time period, counting the total output value corresponding to each user account of the service obtained in the target time period, and obtaining a second number of user accounts with the maximum total output value; and/or the presence of a gas in the gas,

and calculating the profit size corresponding to each user account according to the total consumption amount and the total output value corresponding to each user account for purchasing the probabilistic service in the target time period, and acquiring a third number of user accounts with the maximum profit size.

In another aspect, the present application provides an apparatus for data processing, the apparatus comprising:

the system comprises a first acquisition module, a second acquisition module and a service processing module, wherein the first acquisition module is used for acquiring configuration information of the probability service in a target time period, the configuration information comprises theoretical probability corresponding to the probability service, consumption amount required by purchasing the probability service and output value of service provided by the probability service, and the probability service runs in a service server;

a second obtaining module, configured to obtain a consumption log and a service log of the probabilistic service in the target time period, where the consumption log is used to record a situation that a user purchases the probabilistic service in the service server, and the service log is used to record a situation that the service server provides the service to the user;

and the detection module is used for detecting whether the probability service is tampered according to the consumption log and the service log of the probability service in the target time period according to the configuration information.

Optionally, the detection module is configured to:

the detection module is configured to:

Optionally, the detection module is configured to:

Optionally, the apparatus further comprises:

the first selection module is used for selecting a plurality of user accounts meeting preset conditions from the user accounts purchasing the probabilistic service in the target time period according to each consumption log and each service log in the target time period;

a third obtaining module, configured to obtain a device identifier corresponding to each user account in the multiple user accounts to obtain a device identifier set, and count, from the multiple user accounts, the number of user accounts corresponding to each device identifier in the device identifier set;

and the second selection module is used for selecting the equipment identifier of which the number of the user accounts exceeds the number threshold from the equipment identifier set, wherein the equipment corresponding to the selected equipment identifier is abnormal equipment.

the first selection module is configured to:

In another aspect, the present application provides an electronic device, comprising: a processor and a memory. The processor and the memory can be connected through a bus system. The memory is used for storing programs, instructions or codes, and the processor is used for executing the programs, the instructions or the codes in the memory to realize the method.

In another aspect, the present application provides a computer program product comprising a computer program stored in a computer readable storage medium and loaded by a processor to implement the above method.

In another aspect, the present application provides a non-transitory computer-readable storage medium for storing a computer program, which is loaded by a processor to execute the instructions of the method.

The technical scheme provided by the embodiment of the application can have the following beneficial effects:

acquiring configuration information of the probability service in a target time period, wherein the configuration information comprises theoretical probability corresponding to the probability service, consumption amount required by purchasing the probability service and output value of service provided by the probability service; acquiring a consumption log and a service log of the probability service in a target time period, wherein the consumption log is used for recording the condition that a user purchases the probability service in the service server, and the service log is used for recording the condition that the service server provides the service for the user; therefore, according to the configuration information, whether the probabilistic service is falsified or not is detected by the consumption log and the service log of the probabilistic service in the target time period, and when the probabilistic service is detected to be falsified, an alarm can be given in time so that technical personnel of an enterprise can check and process the service server, and the security of the probabilistic service is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

Fig. 1 is a schematic diagram of a network architecture provided in an embodiment of the present application;

FIG. 2 is a flow chart of a method for processing data according to an embodiment of the present disclosure;

FIG. 3 is a flow chart of another method for data processing provided by embodiments of the present application;

FIG. 4 is a flow chart of another method for data processing provided by embodiments of the present application;

fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application.

With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

The terms "first", "second", "third", and the like in the terms provided in the embodiments of the present invention are used for distinguishing concepts having substantially the same functions and functions or similar concepts, so that the terms "first", "second", and "third" in the embodiments of the present invention have no logical or temporal dependency, and do not limit the number and execution order, but only name the differences.

Hereinafter, terms related to the embodiments of the present invention are explained:

the probability service corresponds to a theoretical probability, which means that when the user purchases the probability service, a service server running the probability service determines whether to provide a service corresponding to the probability service for the user based on the theoretical probability. For example, assuming that the theoretical probability corresponding to the probabilistic service is 50%, when the user invests money for purchasing the probabilistic service for the first time, the service server may not provide the service corresponding to the probabilistic service for the user, and when the user invests money for purchasing the probabilistic service for the second time, the service server may provide the service corresponding to the probabilistic service for the user; or, when the user invests the amount of money for purchasing the probabilistic service for the first time, the service server may provide the service corresponding to the probabilistic service for the user, and when the user invests the amount of money for purchasing the probabilistic service for the second time, the service server may not provide the service corresponding to the probabilistic service for the user.

The business server is a server for running probabilistic business in an enterprise, and a large amount of logs can be generated and stored when the business server runs the business. For example, when a user invests money to purchase a probabilistic service, the service server may generate a purchase order and a consumption log, where the consumption log includes information such as a user account of the user, an order identifier of the purchase order, a device identifier of a device used by the user, a log identifier of the consumption log, a service identifier of the probabilistic service, a consumption money, and a consumption time. When a user purchases probability service, the service server determines whether to provide the service corresponding to the probability service for the user based on the theoretical probability corresponding to the probability service, and if the service corresponding to the probability service is determined to be provided, the service server generates a service log, wherein the service log comprises a user account of the user, an equipment identifier of equipment used by the user, an order identifier of the purchase order, a log identifier of the service log, a service identifier of the probability service, the output value of the provided service, the providing time of the service and the like.

Optionally, the service corresponding to the probability service provided by the service server may be a prize, etc. Assuming that the service provided by a certain probability service is a prize, the amount of money can be used to measure the output value of the prize. For example, the value of the prize is 100 yuan, i.e., the value of the output of the service provided by the probability service is 100 yuan.

Optionally, an enterprise often has multiple probabilistic services, which often run on different service servers.

Alternatively, an enterprise often has a central server that can maintain consumption logs and service logs generated by each business server. That is, for any business server in the enterprise, when the business server generates a consumption log or a service log, the business server sends the generated consumption log or service log to the central server. The central server receives and saves the consumption log or the service log.

Optionally, for any probabilistic service in the enterprise, the central server may further store each configuration log corresponding to the probabilistic service. The personnel of the enterprise can configure configuration information of the probability service on the central server, such as configuring a theoretical probability corresponding to the probability service, a consumption amount, an output value of a service provided by the probability service, and the like. Correspondingly, the central server generates a configuration log, wherein the configuration log comprises information such as the service identification of the probability service, the current theoretical probability, the consumption amount, the output value and the configuration time. Technicians often configure configuration information of the probabilistic service in the central server periodically or aperiodically, and the central server generates and stores a configuration log corresponding to the probabilistic service when configuring the probabilistic service each time.

Optionally, for the probabilistic service, the technician configures the probabilistic service for the first time, and the central server correspondingly stores the service identifier, the theoretical probability, the consumption amount, and the output value of the probabilistic service in the corresponding relationship among the service identifier, the theoretical probability, the consumption amount, and the output value. The central server updates the corresponding relation each time the technician reconfigures at least one of the theoretical probability, the consumption amount and the output value corresponding to the probability service. For example, if the technology reconfigures the theoretical probability corresponding to the probabilistic service, the central server obtains the corresponding theoretical probability from the corresponding relationship according to the service identifier of the probabilistic service, and updates the obtained theoretical probability to the reconfigured probability.

Optionally, since the technician may modify the theoretical probability corresponding to the probability service, the theoretical probability corresponding to the same probability service may be different in different time periods. Therefore, the theoretical production proportions corresponding to the probability service are different in different time periods. And the theoretical production ratio corresponding to the probability service in a time period is equal to (W x P)/Q, wherein W is the output value corresponding to the service provided by the probability service, P is the theoretical probability corresponding to the probability service in the time period, and Q is the consumption amount to be invested by the user for purchasing the probability service. Assuming that W is 100, P is 20%, and Q is 50, the theoretical production percentage is calculated to be 0.4. The theoretical production proportion reflects the profit of the probability business, and the theoretical production proportion of the probability business is smaller than 1, which indicates that the enterprise may generate profit when operating the probability business. The smaller the theoretical production proportion is, the better the profit of the probability service is.

Referring to fig. 1, an embodiment of the present invention provides a network architecture, including: the system comprises a central server and at least one business server;

each business server in the at least one business server is used for running probability business, and a communication connection is established between each business server and the central server.

Optionally, the central server stores a correspondence between the service identifier, the theoretical probability, the consumption amount, and the output value.

For any service server, when a user purchases a probabilistic service running in the service server on the service server, the service server inquires the theoretical probability, the consumption amount and the output value corresponding to the probabilistic service from the central server according to the service identification of the probabilistic service, and simultaneously generates a purchase order and a consumption log. The purchase order includes information such as a user account of the user, a consumption amount to be deducted and the like, and the consumption log includes information such as the user account of the user, a device identifier of a device used by the user, a log identifier of the consumption log, a service identifier of the probabilistic service, the consumption amount corresponding to the probabilistic service, an order identifier and consumption time of the purchase order and the like. The service server then sends a fee deduction request to the central server, the fee deduction request including the consumption log. The central server receives the fee deduction request, stores the consumption log and sends a fee deduction agreement response to the service server.

And the service server receives the fee deduction agreement response, deducts the consumption amount from the user account of the user and saves the consumption log. And then the service server determines whether to provide the service corresponding to the probability service for the user according to the theoretical probability corresponding to the probability service, and if the service corresponding to the probability service is determined to be provided, a service log is generated and comprises a user account of the user, a device identifier of the device used by the user, a log identifier of the service log, a service identifier of the probability service, an order identifier of the purchase order, the output value of the service provided by the probability service, the service time for providing the service and the like. The service server sends an issuing request to the central server, wherein the issuing request comprises the service log. The central server receives the issuing request, stores the service log and sends an issuing approval response to the service server. And the service server receives the issuing approval response, provides the service corresponding to the probability service for the user and stores the service log.

Among them, it should be noted that: the internal personnel or hacker of the enterprise may tamper with the configuration information of the probabilistic service running in the service server, for example, the theoretical probability, the consumption amount and/or the production value corresponding to the probabilistic service may be tampered, so that the service server runs the probabilistic service according to the tampered theoretical probability, the consumption amount and/or the production value.

The actual production ratio of the probability service can be increased by increasing the theoretical probability corresponding to the probability service, reducing the consumption amount corresponding to the probability service or increasing the output value corresponding to the probability service, when the actual production ratio is greater than 1, the insiders and the hackers can register a plurality of user accounts on one device or a plurality of devices, and purchase the probability service through different user accounts, so that the service server can provide a large amount of services corresponding to the probability service, and the purpose of arbitrage is achieved. However, at present, probability service is tampered, which often cannot be found in time, resulting in lower security of the probability service.

In order to solve the technical problem, in the embodiment of the present application, the anomaly of the probabilistic service may be discovered by processing the consumption log and the service log stored in the corresponding central server and/or the consumption log and the service log stored in each service server, so that a technician in an enterprise may timely perform repair processing on the configuration information of the probabilistic service or the service server. The detailed implementation of the data processing will be described in detail in the embodiment shown in fig. 3.

Referring to fig. 2, an embodiment of the present application provides a data processing method, where the method includes:

step 101: and acquiring configuration information of the probability service in a target time period, wherein the configuration information comprises theoretical probability corresponding to the probability service, consumption amount required by purchasing the probability service and output value of service provided by the probability service, and the probability service runs in a service server.

Step 102: and acquiring a consumption log and a service log of the probability service in a target time period, wherein the consumption log is used for recording the condition that a user purchases the probability service in a service server, and the service log is used for recording the condition that the service server provides the service for the user.

Step 103: and according to the configuration information, detecting whether the probabilistic service is tampered by the consumption log and the service log of the probabilistic service in the target time period.

In the embodiment of the application, the configuration information of the probability service in the target time period is obtained, wherein the configuration information comprises the theoretical probability corresponding to the probability service, the consumption amount required by purchasing the probability service and the output value of the service provided by the probability service; acquiring a consumption log and a service log of the probability service in a target time period, wherein the consumption log is used for recording the condition that a user purchases the probability service in the service server, and the service log is used for recording the condition that the service server provides the service for the user; therefore, according to the configuration information, whether the probabilistic service is falsified or not is detected by the consumption log and the service log of the probabilistic service in the target time period, and when the probabilistic service is detected to be falsified, an alarm can be given in time so that technical personnel of an enterprise can check and process the service server, and the security of the probabilistic service is improved.

Referring to fig. 3, an embodiment of the present application provides a data processing method, which is applied to the network architecture shown in fig. 1, and the method includes:

step 201: and the central server and the business server synchronize consumption logs and service logs.

The service server is any one of the service servers in the network architecture shown in fig. 1, and a probabilistic service is operated in the service server.

And the central server acquires the consumption log and the service log belonging to the probability service from the consumption log and the service log which are locally stored according to the service identifier of the probability service. The consumption log and the service log including the service identification of the probabilistic service are the consumption log and the service log belonging to the probabilistic service.

Optionally, the central server obtains a target consumption log, where the target consumption log is a consumption log stored in the service server but not stored in the central server, and the target consumption log may be a consumption log generated by the service server deducting the fee of the user without agreement of the central server, so that a return command is sent to the service server, where the return command includes the target consumption log. And the service server receives the return command, returns the deducted fee to the user corresponding to the user account according to the consumption amount and the user account in the target consumption log, and deletes the target consumption log.

It is possible that the probabilistic service in the service server is hacked or tampered with, resulting in the service server deducting fees and generating consumption logs without the central server agreeing when running the probabilistic service.

Optionally, the central server may query a consumption log from the service server, query whether a consumption log corresponding to the log identifier is stored locally according to the log identifier included in the consumption log, and determine that the consumption log is a target consumption log if the consumption log is not stored locally. And then continuously inquiring the next consumption log from the service server until all the consumption logs in the service server are inquired.

Optionally, the central server obtains a target service log, where the target service log is stored in the central server but not stored in the service log in the service server. The reasons for this may be: the service server has sent the issuing request to the central server, but after receiving the issuing approval response sent by the central server, the service server does not provide the service corresponding to the probabilistic service to the user. And at the moment, the central server sends a control command to the business server, the control command comprises a target service log, the business server receives the target service log, provides a service corresponding to the probability service for a user corresponding to a user account included in the target service log, and stores the target service log.

It is possible that the probabilistic service in the service server is hacked or tampered, so that the service server does not provide the service corresponding to the probabilistic service to the user after receiving the release approval response.

Therefore, when the central server finds that the locally stored consumption log of the probabilistic service is inconsistent with the message log of the probabilistic service stored by the service server running the probabilistic service, and/or when the central server finds that the locally stored service log of the probabilistic service is inconsistent with the service log of the probabilistic service stored by the service server running the probabilistic service, an alarm can be given to enable a technician to check the service server.

Step 202: the central server acquires configuration information of the probability service in a target time period, wherein the configuration information comprises theoretical probability, consumption amount and output value corresponding to the probability service.

The central server locally stores configuration logs, and locally acquires each configuration log belonging to the probability service according to the service identifier of the probability service, wherein any acquired configuration log comprises information such as the service identifier, the theoretical probability, the configuration time and the like of the probability service. And selecting two adjacent configuration logs for configuring the probability service from the configuration logs belonging to the probability service, wherein the two selected configuration logs comprise two configuration times, a time period between the two configuration times is taken as a target time period, and the configuration information of the probability service in the target time period is obtained from the configuration logs comprising the starting time of the target time period.

The theoretical probability, the consumption amount and the output value corresponding to the probabilistic service included in the configuration log can be used as the configuration information of the probabilistic service in the target time period.

For example, assuming that configuration logs of the probabilistic service are configured for two adjacent times, wherein one configuration log comprises the configuration time of 2019-8-19, and the other configuration log comprises the configuration time of 2019-9-19, the target time period is 2019-8-9 to 2019-9-19, and the configuration information of the probabilistic service can be obtained from the configuration logs generated by configuring the probabilistic service for the days 2019-8-19.

Step 203: and the central server acquires the theoretical production proportion of the probability service in the target time period according to the configuration information of the probability service in the target time period.

And calculating that the theoretical production proportion of the probability service in the target time period is equal to (W x P)/Q, wherein W is the output value corresponding to the service provided by the probability service in the target time period, P is the theoretical probability corresponding to the probability service in the target time period, and Q is the consumption amount consumed by the user for purchasing the probability service in the target time period.

Step 204: and the central server acquires the actual production proportion and the actual probability of the probability service in the target time period according to the consumption log and the service log of the probability service in the target time period.

In this step, the method can be implemented by the following steps 2041 to 2043, where the steps 2041 to 2043 are:

2041: the central server obtains a consumption log and a service log of the probabilistic service generated in the target time period.

The central server locally acquires a consumption log and a service log which comprise the service identifier of the probability service to obtain the consumption log and the service log which belong to the probability service. And obtaining each consumption log of which the consumption time is in a target time period from the consumption log belonging to the probability service, and obtaining each service log of which the service providing time is in the target time period from the service log belonging to the probability service, so as to obtain the consumption log and the service log of the probability service generated in the target time period.

2042: and the central server acquires the actual production proportion of the probability service in the target time period according to the consumption log and the service log of the probability service generated in the target time period.

And the central server counts the consumption amount included in each consumption log of the probability service to obtain the total consumption amount. And counting the output value included in each service log of the probability service to obtain the total output value. And calculating the ratio of the total output value to the total consumption amount to obtain the actual production proportion of the probability service in the target time period.

2043: and the central server acquires the actual probability of the probability service in the target time period according to the consumption log and the service log of the probability service generated in the target time period.

The central server counts the consumption log number of the probability service generated in the target time period, counts the service log number of the probability service generated in the target time period, and calculates the ratio of the service log number to the total consumption log number to obtain the actual probability of the probability service in the target time period.

The consumption log number is the total number of times of purchasing probability service from the service server by all users in the target time period, and the service log number is the total number of times of providing the service corresponding to the probability service by the service server in the target time period.

Step 205: and the central server determines whether the probability service is tampered in the target time period according to the theoretical probability and the theoretical production proportion of the probability service in the target time period and the actual probability and the actual production proportion in the target time period.

The central server calculates a probability difference value between the theoretical probability and the actual probability of the probability service and calculates an operation ratio difference value between the theoretical operation ratio and the actual operation ratio of the probability service, and under the condition that the probability difference value exceeds a probability threshold value and/or the operation ratio difference value exceeds an operation ratio threshold value, the probability service is determined to be tampered in a target time period.

Optionally, the probability threshold is equal to 0.05, 0.06, 0.07, 0.08, 0.09, or 0.1 equivalents, and the on-stream ratio threshold is equal to 0.05, 0.06, 0.07, 0.08, 0.09, or 0.1 equivalents.

In the target time period, if the configuration information of the probabilistic service is not tampered, that is, the consumption amount, the output value and the theoretical probability of the probabilistic service are not tampered, the difference between the calculated actual production proportion and the theoretical production proportion is smaller, and the difference between the calculated actual probability and the theoretical probability is smaller. Therefore, under the condition that the probability difference exceeds the probability threshold and/or the production proportion difference exceeds the production proportion threshold, the probability service is determined to be tampered in the target time period, and then a technician is informed to process the probability service or check a service server running the probability service.

The central server may repeatedly perform the operations 202 to 205 described above to determine whether the probabilistic service has been tampered with in different time periods.

Optionally, in this embodiment of the present application, through the following steps 301 to 303, an abnormal device may be identified from devices corresponding to a user account for purchasing a probabilistic service in a target time period, and then an alarm is given, where the abnormal device may be a device used by a hacker or the like, and the hacker or the like uses the abnormal device to perform arbitrage operation from a service server.

Referring to fig. 4, the steps 301 to 303 are:

step 301: and the central server selects a plurality of user accounts meeting preset conditions from the user accounts purchasing the probabilistic service in the target time period according to each consumption log and each service log in the target time period.

The plurality of user accounts may include at least one of the following three user accounts.

For the first user account, the central server counts the total consumption amount corresponding to each user account purchasing the probabilistic service in the target time period according to each consumption log in the target time period, and obtains a first number of user accounts with the maximum total consumption amount.

Optionally, when implemented: and obtaining each consumption log comprising the same user account in each consumption log of the probabilistic service in a target time period, namely obtaining each consumption log corresponding to the user account, and counting the consumption amount included in each consumption log corresponding to the user account to obtain the total consumption amount of the user account in the target time period. And obtaining the total consumption amount of each user account in the target time period according to the mode, and selecting a first number of user accounts with the maximum total consumption amount from the user accounts in the target time period.

For the second user account, the central server counts the total output value corresponding to each user account of the service obtained in the target time period according to each service log in the target time period, and obtains a second number of user accounts with the maximum total output value, wherein the service is the service corresponding to the probability service.

Optionally, when implemented: and obtaining each service log comprising the same user account in each service log of the probabilistic service in a target time period, namely obtaining each service log corresponding to the user account, and counting the output value included in each service log corresponding to the user account to obtain the total output value of the user account in the target time period. And obtaining the total output value of each user account in the target time period according to the mode, and selecting a second number of user accounts with the maximum total output value from the user accounts in the target time period.

For the third user account, the central server calculates the profit size corresponding to each user account according to the total consumption amount and the total output value corresponding to each user account purchasing the probabilistic service in the target time period, and obtains a third number of user accounts with the largest profit size.

Optionally, when implemented: and calculating the profit size corresponding to each user account according to the total consumption amount and the total output value corresponding to each user account, and selecting a third number of user accounts with the largest profit size from the user accounts in the target time period.

Step 302: the central server obtains the device identification corresponding to each user account in the plurality of user accounts to obtain a device identification set, and counts the number of the user accounts corresponding to each device identification in the device identification set from the plurality of user accounts.

Optionally, the device identifier corresponding to each user account in the first number of user accounts is obtained from the consumption log of the first number of user accounts.

Optionally, the device identifier corresponding to each user account in the second number of user accounts is obtained from the service log corresponding to the second number of user accounts.

Optionally, the device identifier corresponding to each user account in the third number of user accounts is obtained from the service log corresponding to the third number of user accounts.

The device identification set comprises device identifications corresponding to each user account in a first number of user accounts, device identifications corresponding to each user account in a second number of user accounts, and/or device identifications corresponding to each user account in a third number of user accounts.

Optionally, the number of the user accounts corresponding to the same device identifier is determined according to the device identifiers corresponding to the first number of user accounts, the device identifiers corresponding to the second number of user accounts and the device identifiers corresponding to the third number of user accounts, so that the number of the user accounts corresponding to the device identifier is obtained. The number of the user accounts corresponding to the device identifier is less than 1, which indicates that a plurality of user accounts log in the device corresponding to the device identifier, and the device uses the user accounts to purchase the probabilistic service from the service server. According to the mode, the number of the user accounts corresponding to each device identifier in each device identifier set in the device identifier set is obtained.

Step 303: and selecting the equipment identifier of which the number of the user accounts exceeds the number threshold from the equipment identifier set, wherein the equipment corresponding to the selected equipment identifier is abnormal equipment.

Under the condition that the number of user accounts corresponding to a certain equipment identifier exceeds a number threshold value, it is indicated that a hacker and other people may tamper with the probability service running in the service server, and a large number of user accounts are logged in the equipment corresponding to the equipment identifier to purchase services corresponding to the probability service so as to collect benefits, so that the central server can give an alarm to enable technicians to check the service server, analyze and select abnormal equipment corresponding to the equipment identifier, analyze the equipment actually used by the hacker and other people to collect the abnormal equipment into a blacklist.

In the embodiment of the present application, the operations in steps 201 to 205 are performed on each service server in the enterprise to detect whether the probabilistic service running in each service server is tampered.

Optionally, the first number, the second number and the third number are all equal, for example, the first number, the second number and the second number are all 100, 200 or 300.

In the embodiment of the application, the configuration information of the probability service in the target time period is obtained, wherein the configuration information comprises the theoretical probability, the consumption amount and the output value corresponding to the probability service; acquiring the theoretical production proportion of the probability service in a target time period according to the configuration information of the probability service in the target time period; and acquiring the actual production proportion and the actual probability of the probability service in the target time period according to the consumption log and the service log of the probability service in the target time period. Therefore, whether the probability service is falsified in the target time period is determined according to the theoretical probability and the theoretical production proportion of the probability service in the target time period and the actual probability and the actual production proportion in the target time period, and when the falsification is detected, an alarm can be given in time to enable technicians of an enterprise to check and process the service server, so that the safety of the probability service is improved. In addition, according to each consumption log and each service log in a target time period, a plurality of user accounts meeting preset conditions are selected from user accounts purchasing the probabilistic service in the target time period, an equipment identifier corresponding to each user account in the user accounts is obtained, an equipment identifier set is obtained, the number of the user accounts corresponding to each equipment identifier in the equipment identifier set is counted from the user accounts, an equipment identifier with the number of the user accounts exceeding a number threshold value is selected from the equipment identifier set, and equipment corresponding to the selected equipment identifier is abnormal equipment. Hackers and other personnel tamper with the probability service running in the service server, log in a large number of user accounts on the abnormal equipment to purchase services corresponding to the probability service so as to collect benefits, and after obtaining the abnormal equipment, can give an alarm to the abnormal equipment so that technicians can further check the service server and process the abnormal equipment, for example, the abnormal equipment is pulled into a blacklist, so that the safety of the probability service is further improved.

The following are embodiments of the apparatus of the present application that may be used to perform embodiments of the method of the present application. For details which are not disclosed in the embodiments of the apparatus of the present application, reference is made to the embodiments of the method of the present application.

Referring to fig. 5, an embodiment of the present application provides an apparatus 400 for data processing, where the apparatus 400 includes:

a first obtaining module 401, configured to obtain configuration information of a probabilistic service in a target time period, where the configuration information includes a theoretical probability corresponding to the probabilistic service, a consumption amount required for purchasing the probabilistic service, and a yield value of a service provided by the probabilistic service, and the probabilistic service operates in a service server;

a second obtaining module 402, configured to obtain a consumption log and a service log of the probabilistic service in the target time period, where the consumption log is used to record a situation that a user purchases the probabilistic service in the service server, and the service log is used to record a situation that the service server provides the service to the user;

a detecting module 403, configured to detect, according to the configuration information, whether the probabilistic service is tampered with in the consumption log and the service log of the probabilistic service in the target time period.

Optionally, the detecting module 403 is configured to:

the detecting module 403 is configured to:

Optionally, the detecting module 403 is configured to:

Optionally, the apparatus 400 further includes:

the first selection module is configured to:

In the embodiment of the application, a first obtaining module obtains configuration information of the probability service in a target time period, wherein the configuration information comprises a theoretical probability corresponding to the probability service, a consumption amount required by purchasing the probability service and an output value of a service provided by the probability service; the second acquisition module acquires a consumption log and a service log of the probabilistic service in a target time period, wherein the consumption log is used for recording the condition that a user purchases the probabilistic service in the service server, and the service log is used for recording the condition that the service server provides the service for the user; therefore, the detection module detects whether the probabilistic service is tampered according to the configuration information and the consumption log and the service log of the probabilistic service in the target time period, and can give an alarm in time when the probabilistic service is detected to be tampered, so that technical personnel of an enterprise can check and process the service server, and the security of the probabilistic service is improved.

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

Fig. 6 is a block diagram illustrating an apparatus 500 for data processing in accordance with an example embodiment. For example, the apparatus 500 may be provided as a server, such as the central server described above. Referring to fig. 6, apparatus 500 includes a processing component 522 that further includes one or more processors and memory resources, represented by memory 532, for storing instructions, such as application programs, that are executable by processing component 522. The application programs stored in memory 532 may include one or more modules that each correspond to a set of instructions. Further, the processing component 522 is configured to execute instructions to perform the above-described method of data processing.

The apparatus 500 may further include a power supply component 526 configured to perform power management of the apparatus 500, a wired or wireless network interface 550 configured to connect the apparatus 500 to a network, and an input/output (I/O) interface 558 the apparatus 500 may be operable based on an operating system stored in the memory 532, such as Windows server, Mac OS XTM, UnixTM, &ltttttranslation = L "&gtt translation &/t &gttinx, FreeBSDTM, or the like.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A method of data processing, the method comprising:

2. The method of claim 1, wherein the detecting whether the probabilistic service has been tampered with based on the configuration information and the consumption log and the service log of the probabilistic service in the target time period comprises:

3. The method of claim 2, wherein the consumption log comprises the consumption amount and the consumption time, and the service log comprises a production value size of the service and a provision time for providing the service;

4. The method of claim 3, wherein the obtaining the actual probability of the probabilistic service based on the consumption log and the service log of the probabilistic service over the target time period comprises:

5. The method of claim 2, wherein the detecting whether the probabilistic traffic is tampered within the target time period according to the theoretical production proportion, the theoretical probability, the actual production proportion, and the actual probability comprises:

6. The method of any of claims 1-5, wherein the obtaining the consumption log and the service log of the probabilistic traffic over the target time period further comprises:

7. The method of claim 6, wherein the consumption log comprises the consumption amount, the consumption time, a user account and a device identifier corresponding to the user account, wherein the service log comprises the user account, the device identifier corresponding to the user account, a value of output of the service and a providing time for providing the service,

8. An apparatus for data processing, the apparatus comprising:

9. The apparatus of claim 8, wherein the detection module is to:

10. The apparatus of claim 9, wherein a consumption log comprises the consumption amount and consumption time, a service log comprises a magnitude of a yield value of the service and a provision time for providing the service;

the detection module is configured to:

11. The apparatus of claim 10, wherein the detection module is to:

12. The apparatus of claim 9, wherein the detection module is to:

13. The apparatus of any one of claims 8-12, further comprising:

14. The apparatus of claim 13, wherein the consumption log comprises the consumption amount, the consumption time, a user account and a device identifier corresponding to the user account, wherein the service log comprises the user account, the device identifier corresponding to the user account, a value of output of the service and a providing time for providing the service,

the first selection module is configured to: