CN114257411A - Transaction flow control method, apparatus, device, medium and computer program product - Google Patents
Transaction flow control method, apparatus, device, medium and computer program product Download PDFInfo
- Publication number
- CN114257411A CN114257411A CN202111401046.0A CN202111401046A CN114257411A CN 114257411 A CN114257411 A CN 114257411A CN 202111401046 A CN202111401046 A CN 202111401046A CN 114257411 A CN114257411 A CN 114257411A
- Authority
- CN
- China
- Prior art keywords
- service
- historical
- flow control
- target type
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 238000004590 computer program Methods 0.000 title claims description 48
- 230000004044 response Effects 0.000 claims description 138
- 230000000875 corresponding effect Effects 0.000 claims description 62
- 230000002596 correlated effect Effects 0.000 claims description 19
- 230000000977 initiatory effect Effects 0.000 claims description 15
- 238000012935 Averaging Methods 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 10
- 238000005070 sampling Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 9
- 230000001276 controlling effect Effects 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 238000011217 control strategy Methods 0.000 description 5
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000004913 activation Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 230000001960 triggered effect Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/20—Traffic policing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
- H04L47/2425—Traffic characterised by specific attributes, e.g. priority or QoS for supporting services specification, e.g. SLA
- H04L47/2433—Allocation of priorities to traffic types
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/02—Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
- H04L63/0227—Filtering policies
- H04L63/0236—Filtering by address, protocol, port number or service, e.g. IP-address or URL
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
- H04L63/101—Access control lists [ACL]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/10—Network architectures or network communication protocols for network security for controlling access to devices or network resources
- H04L63/105—Multiple levels of security
Abstract
The application relates to a transaction flow control method, a transaction flow control device, computer equipment and a storage medium. The method comprises the following steps: acquiring real-time transaction index data of a target type of service; acquiring historical transaction index data of a target type of service; and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result. The method can meet the requirements of transaction flow control of different service types and fit the operation condition of a financial system.
Description
Technical Field
The present application relates to the field of big data analysis technologies, and in particular, to a method and an apparatus for controlling transaction flow, a computer device, a storage medium, and a computer program product.
Background
In the financial system, the purpose of transaction flow control is to limit the transaction concurrency amount, avoid the condition that the service response is slow and even stopped due to the overlarge transaction concurrency amount, and ensure the normal operation of the financial system.
In the prior art, when transaction flow control is performed, a rated transaction flow control threshold is set based on a unified and standardized transaction flow control method, when the transaction amount in a financial system exceeds the rated transaction flow control threshold, flow control is triggered, and access is denied to a transaction request exceeding the flow control threshold.
However, in the financial system, the service types are various, and the transaction flow control method which is unified and standardized is adopted, so that the transaction flow control requirements of different service types cannot be met, and the operation condition of the financial system cannot be accurately fitted.
Disclosure of Invention
In view of the above, it is necessary to provide a transaction flow control method, apparatus, computer device, storage medium and computer program product capable of meeting the transaction flow control requirements of different service types.
In a first aspect, a transaction flow control method is provided, the method comprising:
acquiring real-time transaction index data of a target type of service;
acquiring historical transaction index data of a target type of service;
and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
In one embodiment, the real-time transaction index data includes a real-time service response duration, the historical transaction index data includes a historical average service response duration, and the adjusting the current flow control level of the target type service according to the comparison result includes:
determining a first ratio between the real-time service response duration and the historical average service response duration;
and if the first ratio is larger than the first preset ratio, reducing the current flow control level of the service of the target type, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, obtaining historical transaction index data for a target type of service includes:
acquiring historical service transaction data, wherein the historical service transaction data comprises historical service response time of a plurality of target types of services in a first historical time period;
and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the method further comprises:
acquiring an initial regulation and control level of a target type service;
updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration;
and when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio, adjusting the flow control level of the target type service to be an initial regulation level.
In one embodiment, the real-time transaction index data includes real-time service data volume, the historical transaction index data includes historical service data volume, and the adjusting the current flow control level of the target type service according to the comparison result includes:
determining a second ratio between the real-time service data volume and the historical service data volume;
if the second ratio is larger than a third preset ratio, judging whether a hacker attack condition is met;
and if the hacker attack condition is not met, improving the current flow control level of the target type service, wherein the flow control level is positively correlated with the service concurrency number.
In one embodiment, obtaining historical transaction index data for a target type of service includes:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period;
and taking the maximum historical business transaction data volume as the historical business data volume.
In one embodiment, determining whether the hacking condition is satisfied includes:
judging whether the IP address of the equipment initiating the target type service is in an IP address blacklist or not;
if not, determining that the hacking condition is not met.
In one embodiment, the method further comprises:
acquiring IP addresses corresponding to services occurring in a preset time period respectively;
counting the business transaction data volume corresponding to each IP address, and comparing the business transaction data volume corresponding to each IP address with a preset threshold value;
and if the business transaction data volume corresponding to a certain IP address is larger than a preset threshold value and the certain IP address is not positioned in the IP address white list, adding the certain IP address into the IP address black list.
In one embodiment, the method further comprises:
and determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
In a second aspect, there is provided a transaction flow control device, comprising:
the first acquisition module is used for real-time transaction index data of the target type service and historical transaction index data of the target type service;
and the flow control module is used for comparing the real-time transaction index data with the historical transaction index data and adjusting the current flow control level of the target type service according to the comparison result.
In one embodiment, the real-time transaction index data includes a real-time service response duration, the historical transaction index data includes a historical average service response duration, and the flow control module includes:
the first ratio determining unit is used for determining a first ratio between the real-time service response duration and the historical average service response duration;
and the first comparison unit is used for reducing the current flow control level of the service of the target type if the first ratio is greater than a first preset ratio, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, the first obtaining module is configured to:
acquiring historical service transaction data, wherein the historical service transaction data comprises historical service response time of a plurality of target types of services in a first historical time period;
and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the apparatus further comprises:
the second acquisition module is used for acquiring the initial regulation and control level of the target type service;
the updating module is used for updating the real-time service response duration of the target type service according to the preset condition and acquiring the updated real-time service response duration;
and the adjusting module is used for adjusting the flow control level of the target type service to be an initial regulation and control level when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio.
In one embodiment, the real-time transaction index data includes real-time traffic data volume, and the historical transaction index data includes historical traffic data volume, and the flow control module includes:
a second ratio determining unit, configured to determine a second ratio between the real-time service data volume and the historical service data volume;
the second comparison unit is used for judging whether a hacker attack condition is met or not if the second ratio is larger than a third preset ratio;
and the level regulating and controlling unit is used for improving the current flow control level of the target type service if the hacker attack condition is not met, wherein the level of the flow control level is positively correlated with the service concurrence quantity.
In one embodiment, the first obtaining module is configured to:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period;
and taking the maximum historical business transaction data volume as the historical business data volume.
In one embodiment, the second comparing unit is configured to determine whether the IP address of the device initiating the target type of service is located in an IP address blacklist, and if not, determine that the hacking condition is not satisfied.
In one embodiment, the apparatus further comprises:
the IP address acquisition module is used for acquiring IP addresses corresponding to services occurring in a preset time period;
the IP address counting module is used for counting the business transaction data volume corresponding to each IP address and comparing the business transaction data volume corresponding to each IP address with a preset threshold value;
and the IP address judging module is used for adding a certain IP address into an IP address blacklist if the business transaction data volume corresponding to the certain IP address is larger than a preset threshold and the certain IP address is not positioned in the IP address white list.
In one embodiment, the apparatus further comprises:
and the flow control grade acquisition module is used for determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
In a third aspect, there is provided a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, implements the transaction flow control method as described in the first aspect above.
In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the transaction flow control method as described in the first aspect above.
In a fifth aspect, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a transaction flow control method as described in the first aspect above.
According to the transaction flow control method, the transaction flow control device, the computer equipment, the storage medium and the computer program product, the real-time transaction index data and the historical transaction index data of the target type of service are obtained, the real-time transaction index data and the historical transaction index data are compared, and the current flow control level of the target type of service is adjusted according to the comparison result. The real-time transaction index data and the historical transaction index data are respectively obtained according to the service types, and the current flow control level of the service is adjusted according to the service types, so that the aim of respectively performing flow control on different service types is fulfilled, and the requirements of transaction flow control on different service types can be met; and because the regulation and control level is adjusted in real time, the dynamic control of the transaction flow is realized, and the operation condition of the system can be better fitted.
Drawings
FIG. 1 is a flow diagram illustrating a transaction flow control method according to one embodiment;
FIG. 2 is a diagram illustrating data interaction in a transaction flow control method according to an embodiment;
FIG. 3 is a schematic flow chart of step 103 in one embodiment;
FIG. 4 is a schematic flow chart of step 102 in one embodiment;
FIG. 5 is a flow diagram illustrating a method of controlling transaction flow in accordance with one embodiment;
FIG. 6 is a schematic flow chart of step 103 in one embodiment;
FIG. 7 is a schematic flow chart of step 102 in one embodiment;
FIG. 8 is a schematic flow chart of step 502 in one embodiment;
FIG. 9 is a flow diagram illustrating a method of controlling transaction flow in accordance with one embodiment;
FIG. 10 is a flow diagram illustrating a method of controlling transaction flow in accordance with one embodiment;
FIG. 11 is a block diagram illustrating the architecture of a transaction flow control device in accordance with one embodiment;
FIG. 12 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It should be noted that, in the embodiments of the present application, the acquisition, storage, use, and processing of data all conform to relevant regulations of national laws and regulations.
In the financial system, the purpose of transaction flow control is to limit the transaction concurrency amount, avoid the condition that the service response is slow and even stopped due to the overlarge transaction concurrency amount, and ensure the normal operation of the financial system.
In the prior art, when transaction flow control is performed, a rated transaction flow control threshold is set based on a unified and standardized transaction flow control method, when the transaction amount in a financial system exceeds the rated transaction flow control threshold, flow control is triggered, and access is denied to a transaction request exceeding the flow control threshold.
The above approach is only applicable to a single generic service scenario. In a financial system, business requirements show personalized and diversified development trends, and business types are various, such as an inquiry type, an investment and financing type, an account opening and activation type, a living service type, a transfer transaction type and the like. The flow control transaction control requirements corresponding to different service types are different, and the unified and standardized transaction flow control method is adopted, so that the transaction flow control requirements of different service types cannot be met, and the operation condition of a financial system cannot be accurately fitted.
In view of this, the embodiments of the present application provide a transaction flow control method, which can meet the transaction flow control requirements of different service types and can accurately conform to the operation conditions of a financial system.
It should be noted that, in the transaction flow control method provided in the embodiment of the present application, the execution subject may be a transaction flow control device, and the transaction flow control device may be implemented as part or all of a database by software, hardware, or a combination of software and hardware.
In the following method embodiments, the execution subject is a server, where the server may be implemented by an independent server or a server cluster composed of multiple servers, and it is understood that the method may also be applied to a system including a terminal and a server, and implemented by interaction between the terminal and the server.
Referring to fig. 1, a flowchart of a transaction flow control method according to an embodiment of the present application is shown. As shown in fig. 1, the transaction flow control method may include the steps of:
The real-time transaction index data includes real-time service response duration, real-time service data volume, and an IP address of a device that initiates a service request. The real-time service response duration refers to real-time per minute average response duration, and the real-time service data volume refers to real-time per minute service transaction data volume.
Wherein, the service type is a financial service type, comprising: query class, transfer transaction class, investment and financing class, account opening and activation class, living service class and the like. Optionally, the financial system stores the business transaction data in blocks according to the type of the business. The terminal can call the required service transaction data from the server.
The data interaction process in the transaction flow control method is shown in fig. 2. Optionally, the terminal is provided with a sampling period, for example, 5min, to collect transaction data, where the transaction data includes a transaction name, a transaction code, a service response duration, a transaction request IP, and a service transaction data volume. And collecting the service transaction data volume of the target type in each period and the service response time length of each service transaction data in real time according to the sampling period. The terminal obtains the service response time length and the service transaction data volume of each service transaction data in the sampling period corresponding to the current moment, averages the service response time lengths of the financial transaction service data in the sampling period, and calculates the average value to be the real-time service response time length. And dividing the service transaction data volume by the sampling period duration to obtain the average transaction volume per minute corresponding to the sampling period, wherein the obtained average transaction volume per minute corresponding to the sampling period is the real-time service data volume.
The historical transaction index data comprises historical average service response duration and historical service data volume.
Optionally, the terminal stores corresponding historical transaction index data for different types of services, and searches for the corresponding historical transaction index data according to the type of the service.
And 103, comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
Optionally, the flow control grades include 5 grades, specifically as follows:
1) level 1, the flow control policy with the largest amount of traffic concurrency, that is, assigning the largest traffic concurrency flow control threshold, for example, 60.
2) And 4, flow control strategy with larger service concurrency quantity, namely, distributing larger service concurrency flow control threshold, for example, 20.
3) Level 3, flow control strategy with medium amount of traffic concurrency, i.e. allocating medium traffic concurrency flow control threshold, e.g. 10.
4) Level 2, flow control strategy with medium amount of traffic concurrency, i.e. allocating medium traffic concurrency flow control threshold, e.g. 5.
5) Level 1, flow control strategy with minimal traffic concurrency, i.e. assigning minimal traffic concurrency flow control threshold, e.g. 2.
Optionally, the terminal sets different flow control level adjustment rules for different services. And determining a flow control grade adjustment rule according to the target type. Comparing the real-time transaction index data with historical transaction index data, comprising: and performing difference operation between the real-time transaction index data and the historical transaction index data, and determining the adjusted grade according to the obtained difference. The current flow control level is then adjusted to the determined adjusted level.
Optionally, the terminal determines a current flow control level of the service of the target type according to the target type, where different service types correspond to different flow control levels.
The embodiment compares the real-time transaction index data with the historical transaction index data by acquiring the real-time transaction index data of the target type service and the historical transaction index data of the target type service, and adjusts the current flow control level of the target type service according to the comparison result. The real-time transaction index data and the historical transaction index data are respectively obtained according to the service types, and the current flow control level of the service is adjusted according to the service types, so that the aim of respectively performing flow control on different service types is fulfilled, and the requirements of transaction flow control on different service types can be met; and because the regulation and control level is adjusted in real time, the dynamic control of the transaction flow is realized, and the operation condition of the financial system can be better fitted.
In the implementation of the present application, the real-time transaction index data includes a real-time service response duration, and the historical transaction index data includes a historical average service response duration, as shown in fig. 3, based on the embodiment shown in fig. 1, this embodiment relates to adjusting the current flow control level of the target type service according to the comparison result in step 103, and includes steps 201 and 202:
in step 201, a first ratio between the real-time service response duration and the historical average service response duration is determined.
Optionally, the first ratio K1The calculation formula of (2) is as follows:
Wherein, the flow control grade is positively correlated with the service concurrency number.
Optionally, the first preset ratio is set to 5. And when the first ratio is larger than a first preset ratio, reducing the current flow control grade by 1 grade. Namely, the real-time service response time AvgCost >5 × BaseTXCost, and the current flow control grade is reduced by 1 grade.
Optionally, the terminal sets a corresponding relationship between the first ratio and the target flow control service level, as shown in table 1 below. The terminal can determine and obtain the target flow control grade in a table look-up mode according to the first ratio. Namely, when the real-time service response time AvgCost is greater than 5 × BaseTXCost, the current flow control grade is adjusted to be level 1; when 2 × BaseTXCost < AvgCost <5 × BaseTXCost, the flow control level is adjusted to level 2.
| First ratio K1 | Target flow control service class |
| K1≥5 | 1 |
| 2≤K1<5 | 2 |
TABLE 1 relationship table of first ratio and target flow control service grade
According to the embodiment, the first ratio between the real-time service response duration and the historical average service response duration is determined, and if the first ratio is greater than the first preset ratio, the current flow control level of the target type service is reduced, so that the current flow control level of the target type service is dynamically adjusted in real time, the calculation is simple, and the calculation amount is small.
In the present embodiment, as shown in fig. 4, based on the embodiment shown in fig. 3, the present embodiment relates to acquiring historical transaction index data of a target type of service in step 102, and includes steps 301 and 302:
Wherein the historical financial transaction data comprises historical business response time lengths of a plurality of target types of business within a first historical time period.
Optionally, the first history segment is a week before the current time.
Optionally, the average transaction time consumption of the target type service in the last week is calculated, where the transaction time consumption is the service response duration, and the historical average service response duration BaseTXCost is obtained.
According to the embodiment of the application, historical business transaction data are obtained, and the average value of a plurality of historical business response time lengths is obtained, so that historical average business response time length is obtained. The statistical operation is carried out on the historical business transaction data, so that the reliability of the historical average business response time length is improved.
In the embodiment of the present application, referring to fig. 5, based on the above embodiment, the transaction flow control method further includes steps 401, 402, and 403:
Optionally, the terminal sets corresponding initial regulation and control levels for different services according to the service types of the services, for example, the initial regulation and control level of the query service is 4 levels, the initial regulation and control level of the transfer transaction service is 4 levels, and the initial regulation and control level of the investment and financing service is 3 levels; the regulation and control level of the life service type business is 3 level; the initial regulation and control level of the account opening activation service is level 2.
And 402, updating the real-time service response time of the target type service according to the preset condition and acquiring the updated real-time service response time.
Optionally, the terminal is provided with a sampling period, for example, 5min, and the corresponding time of each sampling point is obtained according to the sampling interval. The preset condition is to judge whether the next sampling point is reached. And when the terminal detects that the next sampling point is reached, updating the real-time service response time of the target type service.
Optionally, the second preset ratio is equal to the first preset ratio in size. For example, the second preset ratio is 5, that is, when the real-time service response duration AvgCost <5 × BaseTXCost, the flow control level of the target type of service is restored to the initial regulation level.
The embodiment updates the real-time service response time of the target type service according to the preset condition and obtains the updated real-time service response time, when the ratio of the updated real-time service response time to the historical average service response time is smaller than a second preset ratio, the flow control grade of the target type service is adjusted to be the initial regulation and control grade, so that the real-time updating of the real-time service response time is realized, and when the real-time service response time is recovered to be in a normal state, the flow control grade is recovered to be the initial regulation and control grade, so that the aim of dynamically adjusting the flow control strategy is fulfilled.
In the embodiment of the present application, the real-time transaction index data includes a real-time service data volume, and the historical transaction index data includes a historical service data volume, referring to fig. 6, based on the embodiment shown in fig. 1, this embodiment relates to adjusting the current flow control level of the target type service according to the comparison result in step 103, and includes step 501, step 502, and step 503:
Optionally, the second ratio K2The calculation formula is as follows:
When the real-time service data volume of the system is greatly increased, a hacker may attack the system by using a financial transaction vulnerability, and a normal transaction increase may be caused by financial activities (such as double eleven sales promotion, commemorative currency distribution and the like).
Optionally, the third preset ratio is set to 5. When the real-time service data volume TPM >5 × BaseTPM, a hacking attack may occur, and it is necessary to further determine whether there is a hacking attack in the current situation.
And 503, if the hacking condition is not met, improving the current flow control level of the target type service.
Wherein, the flow control grade is positively correlated with the service concurrency number.
Optionally, the step of improving the current flow control level of the target type service includes: and improving the current flow control level of the target type service by 1 level.
The embodiment determines a second ratio between the real-time service data volume and the historical service data volume, if the second ratio is greater than a third preset ratio, whether a hacking condition is met is judged, if the hacking condition is not met, the current flow control grade of the target type service is improved, and as the flow control grade is properly improved for the service transaction volume without finding abnormal IP under the condition of large real-time service data volume, the concurrent requirement during special financial activities is timely met.
In the embodiment of the present application, referring to fig. 7, based on the embodiment shown in fig. 7, the embodiment relates to obtaining historical transaction index data of a target type service in step 102, and includes steps 601 and 602:
Alternatively, the second historical period of time may be set to one week prior to the current time.
Optionally, the terminal obtains the target type of service transaction data volume of each hour in the second historical time period, and obtains a service transaction data volume curve of each hour. The peak of the curve and the time point corresponding to the peak, for example, the nth hour, are searched. And then calculating the service transaction data volume in the period from n-1 to n +1 hour, and dividing the service transaction data volume by 2 to obtain the average transaction volume in the period from n-1 to n +1 hour, namely the maximum historical service transaction data volume.
Optionally, the terminal obtains a peak time point corresponding to each day in a second preset time period, and then takes 1 time period with the corresponding peak time point as a midpoint every day as a peak time period, where the length of the peak time period is 2 hours, for example, when the peak time of a certain day is 10:00, the peak time period is 9: 00-11: 00. and calculating the average transaction amount of the peak time period of each day, and then averaging the average transaction amount of the peak time period of each day to obtain the transaction data volume which is the maximum historical service transaction data volume.
And step 602, taking the maximum historical business transaction data volume as the historical business data volume.
In the embodiment, the maximum historical service transaction data volume of the target type service in the second historical time period is obtained and is used as the historical service data volume, and the historical service data volume is obtained in a statistical mode, so that the reliability of using the historical service data volume as the flow control level adjustment index is improved.
In the embodiment of the present application, referring to fig. 8, based on the embodiment shown in fig. 6, the present embodiment relates to determining whether the hacking condition is satisfied in step 502, and includes steps 701 and 702:
Optionally, the terminal stores an IP address blacklist. Matching the IP address of the equipment initiating the target type service with the information in the IP address blacklist, and judging whether the IP address of the equipment initiating the target type service is positioned in the IP address blacklist or not according to whether the matching is successful or not
And step 702, if not, determining that the hacking condition is not met.
When the IP address of the device initiating the target type service is not in the IP address blacklist, the IP address of the device initiating the target type service can be judged to be normal, and hacker attack does not exist.
The embodiment determines whether the IP address of the device initiating the target type service is in the IP address blacklist, and if not, determines that the hacker attack condition is not met, so that the safety and the reliability of the financial system for flow control are improved.
In the embodiment of the present application, referring to fig. 9, based on the embodiment shown in fig. 8, the transaction flow control method according to the embodiment further includes steps 801, 802, and 803:
Optionally, the preset time period is a time period that takes a zero point of the current time on the day as a starting point and takes the current time as an end point.
Optionally, the terminal divides the service occurring in the preset time period into multiple types according to the IP address, and obtains the service transaction data volume corresponding to each type, that is, the service transaction data volume corresponding to each IP address.
Wherein the IP address white list includes IP address information of the financial institution partner.
According to the embodiment, the IP addresses corresponding to the services occurring in the preset time period are obtained, the service transaction data volume corresponding to each IP address is counted, the service transaction data volume corresponding to each IP address is compared with the preset threshold value, if the service transaction data volume corresponding to a certain IP address is larger than the preset threshold value, the certain IP address is added into the IP address blacklist, so that when the business transaction volume is increased, the blacklist is sealed for hacker IPs with abnormal transaction volumes, the IP address blacklist is dynamically updated, and the safety of the system is improved.
In the embodiment of the present application, as shown in fig. 10, there is provided a transaction flow control method, including the following steps:
Wherein the historical financial transaction data comprises historical business response time lengths of a plurality of target types of business within a first historical time period.
The real-time transaction index data comprises real-time service response duration and real-time service data volume; different traffic types correspond to different flow control classes.
In step 907, a first ratio between the real-time service response duration and the historical average service response duration is determined.
And step 909, reducing the current flow control level of the target type service.
Wherein, the flow control grade is positively correlated with the service concurrency number.
And the third ratio is the ratio between the updated real-time service response time length and the historical average service response time length.
And step 913, the flow control level of the service is not adjusted.
In step 914, a second ratio between the real-time traffic volume and the historical traffic volume is determined.
In step 915, it is determined whether the second ratio is greater than a third predetermined ratio, if yes, step 916 is performed, otherwise step 913 is performed.
Step 918, the current flow control level of the target type service is improved.
In the embodiment, the real-time transaction index data and the historical transaction index data are respectively obtained according to the service types, and the current flow control level of the service is also adjusted according to the service types, so that the aim of respectively performing flow control on different service types is fulfilled, and the requirements of the transaction flow control of different service types can be met; and because the regulation and control level is adjusted in real time, the dynamic control of the transaction flow is realized, and the operation condition of the financial system can be better fitted. Meanwhile, as a statistical mode is adopted, historical trading index data, namely historical service data volume and historical average service response time, is obtained, and the reliability of the trading index is improved. Meanwhile, the IP addresses corresponding to the services occurring in the preset time period are obtained, the service transaction data volume corresponding to each IP address is counted, the service transaction data volume corresponding to each IP address is compared with the preset threshold value, if the service transaction data volume corresponding to a certain IP address is larger than the preset threshold value, the certain IP address is added into an IP address blacklist, so that when the fact that the transaction volume of a certain service is increased is found, the blacklist is sealed for hacker IPs with abnormal transaction volumes, the IP address blacklist is dynamically updated, and the safety of the system is improved. And the flow control grade is properly improved by the service transaction amount without abnormal IP under the condition of large real-time service data volume, so that the concurrence requirement of special financial activities is met in time.
It should be understood that although the various steps in the flow charts of fig. 1 and 3-10 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1 and fig. 3-10 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least some of the other steps.
In an embodiment of the present application, as shown in fig. 11, there is provided a transaction flow control apparatus including a first obtaining module and a flow control module, wherein:
the first acquisition module is used for real-time transaction index data of the target type service and historical transaction index data of the target type service;
and the flow control module is used for comparing the real-time transaction index data with the historical transaction index data and adjusting the current flow control level of the target type service according to the comparison result.
In one embodiment, the real-time transaction index data includes a real-time service response duration, the historical transaction index data includes a historical average service response duration, and the flow control module includes:
the first ratio determining unit is used for determining a first ratio between the real-time service response duration and the historical average service response duration;
and the first comparison unit is used for reducing the current flow control level of the service of the target type if the first ratio is greater than a first preset ratio, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, the first obtaining module is configured to:
acquiring historical business transaction data, wherein the historical financial transaction data comprises historical business response time of a plurality of target types of businesses in a first historical time period;
and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the apparatus further comprises:
the second acquisition module is used for acquiring the initial regulation and control level of the target type service;
the updating module is used for updating the real-time service response duration of the target type service according to the preset condition and acquiring the updated real-time service response duration;
and the adjusting module is used for adjusting the flow control level of the target type service to be an initial regulation and control level when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio.
In one embodiment, the real-time transaction index data includes real-time traffic data volume and the historical transaction index data includes historical traffic data volume, the flow control module includes:
a second ratio determining unit, configured to determine a second ratio between the real-time service data volume and the historical service data volume;
the second comparison unit is used for judging whether a hacker attack condition is met or not if the second ratio is larger than a third preset ratio;
and the level regulating and controlling unit is used for improving the current flow control level of the target type service if the hacker attack condition is not met, wherein the level of the flow control level is positively correlated with the service concurrence quantity.
In one embodiment, the first obtaining module is configured to:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period;
and taking the maximum historical business transaction data volume as the historical business data volume.
In an embodiment, the second comparing unit is configured to determine whether the IP address of the device initiating the target type of service is located in an IP address blacklist, and if not, determine that the hacking condition is not satisfied.
In one embodiment, the apparatus further comprises:
the IP address acquisition module is used for acquiring IP addresses corresponding to services occurring in a preset time period;
the IP address counting module is used for counting the business transaction data volume corresponding to each IP address and comparing the business transaction data volume corresponding to each IP address with a preset threshold value;
and the IP address judging module is used for adding a certain IP address into an IP address blacklist if the business transaction data volume corresponding to the certain IP address is larger than a preset threshold value.
In one embodiment, the apparatus further comprises:
and the flow control grade acquisition module is used for determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 12. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a transaction flow control method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 12 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring real-time transaction index data of a target type of service;
acquiring historical transaction index data of a target type of service;
and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining a first ratio between the real-time service response duration and the historical average service response duration, wherein the real-time transaction index data comprises the real-time service response duration, and the historical transaction index data comprises the historical average service response duration; and if the first ratio is larger than the first preset ratio, reducing the current flow control level of the service of the target type, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring historical business transaction data, wherein the historical financial transaction data comprises historical business response time of a plurality of target types of businesses in a first historical time period; and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring an initial regulation and control level of a target type service; updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration; and when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio, adjusting the flow control level of the target type service to be an initial regulation level.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
determining a second ratio between the real-time service data volume and the historical service data volume, wherein the real-time transaction index data comprises the real-time service data volume, and the historical transaction index data comprises the historical service data volume; if the second ratio is larger than a third preset ratio, judging whether a hacker attack condition is met; and if the hacker attack condition is not met, improving the current flow control level of the target type service, wherein the flow control level is positively correlated with the service concurrency number.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period; and taking the maximum historical business transaction data volume as the historical business data volume.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
judging whether the IP address of the equipment initiating the target type service is in an IP address blacklist or not; if not, determining that the hacking condition is not met.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring IP addresses corresponding to services occurring in a preset time period respectively; counting the business transaction data volume corresponding to each IP address, and comparing the business transaction data volume corresponding to each IP address with a preset threshold value; and if the business transaction data volume corresponding to a certain IP address is larger than a preset threshold value, adding the certain IP address into an IP address blacklist.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
and determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
In one embodiment, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:
acquiring real-time transaction index data of a target type of service;
acquiring historical transaction index data of a target type of service;
and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a first ratio between the real-time service response duration and the historical average service response duration, wherein the real-time transaction index data comprises the real-time service response duration, and the historical transaction index data comprises the historical average service response duration; and if the first ratio is larger than the first preset ratio, reducing the current flow control level of the service of the target type, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring historical business transaction data, wherein the historical financial transaction data comprises historical business response time of a plurality of target types of businesses in a first historical time period; and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an initial regulation and control level of a target type service; updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration; and when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio, adjusting the flow control level of the target type service to be an initial regulation level.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a second ratio between the real-time service data volume and the historical service data volume, wherein the real-time transaction index data comprises the real-time service data volume, and the historical transaction index data comprises the historical service data volume; if the second ratio is larger than a third preset ratio, judging whether a hacker attack condition is met; and if the hacker attack condition is not met, improving the current flow control level of the target type service, wherein the flow control level is positively correlated with the service concurrency number.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period; and taking the maximum historical business transaction data volume as the historical business data volume.
In one embodiment, the computer program when executed by the processor further performs the steps of:
judging whether the IP address of the equipment initiating the target type service is in an IP address blacklist or not; if not, determining that the hacking condition is not met.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring IP addresses corresponding to services occurring in a preset time period respectively; counting the business transaction data volume corresponding to each IP address, and comparing the business transaction data volume corresponding to each IP address with a preset threshold value; and if the business transaction data volume corresponding to a certain IP address is larger than a preset threshold value, adding the certain IP address into an IP address blacklist.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, performs the steps of:
acquiring real-time transaction index data of a target type of service;
acquiring historical transaction index data of a target type of service;
and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a first ratio between the real-time service response duration and the historical average service response duration, wherein the real-time transaction index data comprises the real-time service response duration, and the historical transaction index data comprises the historical average service response duration; and if the first ratio is larger than the first preset ratio, reducing the current flow control level of the service of the target type, wherein the level of the flow control level is positively correlated with the service concurrency number.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring historical business transaction data, wherein the historical financial transaction data comprises historical business response time of a plurality of target types of businesses in a first historical time period; and carrying out averaging processing on the plurality of historical service response durations to obtain historical average service response durations.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an initial regulation and control level of a target type service; updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration; and when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than a second preset ratio, adjusting the flow control level of the target type service to be an initial regulation level.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a second ratio between the real-time service data volume and the historical service data volume, wherein the real-time transaction index data comprises the real-time service data volume, and the historical transaction index data comprises the historical service data volume; if the second ratio is larger than a third preset ratio, judging whether a hacker attack condition is met; and if the hacker attack condition is not met, improving the current flow control level of the target type service, wherein the flow control level is positively correlated with the service concurrency number.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period; and taking the maximum historical business transaction data volume as the historical business data volume.
In one embodiment, the computer program when executed by the processor further performs the steps of:
judging whether the IP address of the equipment initiating the target type service is in an IP address blacklist or not; if not, determining that the hacking condition is not met.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring IP addresses corresponding to services occurring in a preset time period respectively; counting the business transaction data volume corresponding to each IP address, and comparing the business transaction data volume corresponding to each IP address with a preset threshold value; and if the business transaction data volume corresponding to a certain IP address is larger than a preset threshold value, adding the certain IP address into an IP address blacklist.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (21)
1. A transaction flow control method, the method comprising:
acquiring real-time transaction index data of a target type of service;
acquiring historical transaction index data of the target type of service;
and comparing the real-time transaction index data with the historical transaction index data, and adjusting the current flow control level of the target type of service according to the comparison result.
2. The method according to claim 1, wherein the real-time transaction index data includes a real-time service response duration, the historical transaction index data includes a historical average service response duration, and the adjusting the current flow control level of the target type of service according to the comparison result includes:
determining a first ratio between the real-time service response duration and the historical average service response duration;
and if the first ratio is larger than a first preset ratio, reducing the current flow control level of the target type of service, wherein the flow control level is positively correlated with the service concurrency number.
3. The method of claim 2, wherein obtaining historical transaction index data for the target type of traffic comprises:
obtaining historical business transaction data, wherein the historical business transaction data comprises historical business response time of a plurality of businesses of the target type in a first historical time period;
and carrying out averaging processing on a plurality of historical service response durations to obtain the historical average service response duration.
4. The method of claim 2, further comprising:
acquiring an initial regulation and control level of the target type service;
updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration;
and when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than the second preset ratio, adjusting the flow control level of the target type service to the initial regulation level.
5. The method of claim 1, wherein the real-time transaction index data comprises real-time traffic data volume, the historical transaction index data comprises historical traffic data volume, and the adjusting the current flow control level of the target type of traffic according to the comparison result comprises:
determining a second ratio between the real-time traffic data volume and the historical traffic data volume;
if the second ratio is larger than a third preset ratio, judging whether a hacker attack condition is met;
and if the hacker attack condition is not met, improving the current flow control level of the target type service, wherein the flow control level is positively correlated with the service concurrence number.
6. The method of claim 5, wherein obtaining historical transaction index data for the target type of traffic comprises:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period;
and taking the maximum historical business transaction data volume as the historical business data volume.
7. The method of claim 5, wherein the determining whether the hacking condition is satisfied comprises:
judging whether the IP address of the equipment initiating the target type service is in an IP address blacklist or not;
if not, determining that the hacking condition is not met.
8. The method of claim 7, further comprising:
acquiring IP addresses corresponding to services occurring in a preset time period respectively;
counting the business transaction data volume corresponding to each IP address, and comparing the business transaction data volume corresponding to each IP address with a preset threshold value;
and if the business transaction data volume corresponding to a certain IP address is larger than the preset threshold and the certain IP address is not positioned in an IP address white list, adding the certain IP address into the IP address black list.
9. The method of claim 1, further comprising:
and determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
10. A transaction flow control apparatus, the apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for real-time transaction index data of a target type service and historical transaction index data of the target type service;
and the flow control module is used for comparing the real-time transaction index data with the historical transaction index data and adjusting the current flow control level of the target type of service according to the comparison result.
11. The apparatus of claim 10, wherein the real-time transaction index data comprises a real-time service response duration, wherein the historical transaction index data comprises a historical average service response duration, and wherein the flow control module comprises:
a first ratio determining unit, configured to determine a first ratio between the real-time service response duration and the historical average service response duration;
and the first comparison unit is used for reducing the current flow control level of the target type of service if the first ratio is greater than a first preset ratio, wherein the level of the flow control level is positively correlated with the service concurrency number.
12. The apparatus of claim 11, wherein the first obtaining module is configured to:
obtaining historical business transaction data, wherein the historical business transaction data comprises historical business response time of a plurality of businesses of the target type in a first historical time period;
and carrying out averaging processing on a plurality of historical service response durations to obtain the historical average service response duration.
13. The apparatus of claim 11, further comprising:
the second acquisition module is used for acquiring the initial regulation and control level of the target type service;
the updating module is used for updating the real-time service response duration of the target type service according to preset conditions and acquiring the updated real-time service response duration;
and the adjusting module is used for adjusting the flow control level of the target type service to the initial regulation level when the ratio of the updated real-time service response time length to the historical average service response time length is smaller than the second preset ratio.
14. The apparatus of claim 10, wherein the real-time transaction index data comprises an amount of real-time traffic data and the historical transaction index data comprises an amount of historical traffic data, and wherein the flow control module comprises:
a second ratio determining unit, configured to determine a second ratio between the real-time traffic data volume and the historical traffic data volume;
the second comparison unit is used for judging whether a hacking condition is met or not if the second ratio is larger than a third preset ratio;
and the level regulation and control unit is used for improving the current flow control level of the target type service if the hacker attack condition is not met, wherein the flow control level is positively correlated with the service concurrence quantity.
15. The apparatus of claim 14, wherein the first obtaining module is configured to:
acquiring the maximum historical service transaction data volume of the target type service in a second historical time period;
and taking the maximum historical business transaction data volume as the historical business data volume.
16. The apparatus of claim 14, wherein the second comparing unit is configured to determine whether an IP address of a device initiating the target type of service is in an IP address blacklist, and if not, determine that the hacking condition is not satisfied.
17. The method of claim 16, wherein the apparatus further comprises:
the IP address acquisition module is used for acquiring IP addresses corresponding to services occurring in a preset time period;
the IP address counting module is used for counting the business transaction data volume corresponding to each IP address and comparing the business transaction data volume corresponding to each IP address with a preset threshold value;
and the IP address judging module is used for adding a certain IP address into the IP address blacklist if the business transaction data volume corresponding to the certain IP address is larger than the preset threshold and the certain IP address is not positioned in the IP address white list.
18. The method of claim 10, wherein the apparatus further comprises:
and the flow control grade acquisition module is used for determining the current flow control grade of the service of the target type according to the target type, wherein different service types correspond to different flow control grades.
19. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 9 when executing the computer program.
20. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 9.
21. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 9 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111401046.0A CN114257411A (en) | 2021-11-19 | 2021-11-19 | Transaction flow control method, apparatus, device, medium and computer program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111401046.0A CN114257411A (en) | 2021-11-19 | 2021-11-19 | Transaction flow control method, apparatus, device, medium and computer program product |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114257411A true CN114257411A (en) | 2022-03-29 |
Family
ID=80793082
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111401046.0A Pending CN114257411A (en) | 2021-11-19 | 2021-11-19 | Transaction flow control method, apparatus, device, medium and computer program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114257411A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115002044A (en) * | 2022-05-26 | 2022-09-02 | 平安银行股份有限公司 | Method and device for controlling data transmission, computer equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170148096A1 (en) * | 2010-12-10 | 2017-05-25 | Elasticsearch, Inc. | Method and Apparatus for Detecting Rogue Trading Activity |
| US20170169493A1 (en) * | 2015-12-15 | 2017-06-15 | Costar Realty Information, Inc. | Identification of Entities Based on Deviations in Value |
| CN109885399A (en) * | 2019-01-17 | 2019-06-14 | 平安普惠企业管理有限公司 | Data processing method, electronic device, computer equipment and storage medium |
| CN110874743A (en) * | 2019-10-11 | 2020-03-10 | 支付宝(杭州)信息技术有限公司 | Method and device for determining account transaction risk |
-
2021
- 2021-11-19 CN CN202111401046.0A patent/CN114257411A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170148096A1 (en) * | 2010-12-10 | 2017-05-25 | Elasticsearch, Inc. | Method and Apparatus for Detecting Rogue Trading Activity |
| US20170169493A1 (en) * | 2015-12-15 | 2017-06-15 | Costar Realty Information, Inc. | Identification of Entities Based on Deviations in Value |
| CN109885399A (en) * | 2019-01-17 | 2019-06-14 | 平安普惠企业管理有限公司 | Data processing method, electronic device, computer equipment and storage medium |
| CN110874743A (en) * | 2019-10-11 | 2020-03-10 | 支付宝(杭州)信息技术有限公司 | Method and device for determining account transaction risk |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115002044A (en) * | 2022-05-26 | 2022-09-02 | 平安银行股份有限公司 | Method and device for controlling data transmission, computer equipment and storage medium |
| CN115002044B (en) * | 2022-05-26 | 2024-03-19 | 平安银行股份有限公司 | Method, device, computer equipment and storage medium for controlling data transmission |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111447150A (en) | Access request current limiting method, server and storage medium | |
| EP3869373B1 (en) | Systems and methods for securing access to resources | |
| WO2020140369A1 (en) | Data recovery control method, server and storage medium | |
| CN109299144B (en) | Data processing method, device and system and application server | |
| US8621586B1 (en) | Using baseline profiles in adaptive authentication | |
| CN112099979A (en) | Access control method, device, computer equipment and storage medium | |
| CN114257411A (en) | Transaction flow control method, apparatus, device, medium and computer program product | |
| WO2020248687A1 (en) | Method and apparatus for preventing malicious attack | |
| CN111124315A (en) | Data processing method and device, electronic equipment and storage medium | |
| CN111898147B (en) | Data access control method and device and electronic equipment | |
| CN110569114B (en) | Service processing method, device, equipment and storage medium | |
| CN111694835B (en) | Number section access method, system, equipment and storage medium of logistics electronic bill | |
| CN110191097A (en) | Detection method, system, equipment and the storage medium of login page safety | |
| CN112579576B (en) | Data processing method, device, medium and computing equipment | |
| CN114157482A (en) | Service access control method, device, control equipment and storage medium | |
| CN107948130B (en) | File processing method, server and system | |
| CN112929347A (en) | Frequency limiting method, device, equipment and medium | |
| CN111131393B (en) | User activity data statistical method, electronic device and storage medium | |
| CN111311102A (en) | Resource ratio adjusting method, device, equipment and computer readable storage medium | |
| CN110648208B (en) | Group identification method and device and electronic equipment | |
| CN117422539A (en) | Wind control decision method, device and computer readable storage medium | |
| CN114238729A (en) | Geographical location information determination method, apparatus, device, medium, and program product | |
| CN112148804A (en) | Data preprocessing method, device and storage medium thereof | |
| CN117313133A (en) | Data desensitization method, device, equipment and storage medium | |
| CN117201061A (en) | Method and device for determining abnormal access behaviors |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |