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Service logic learning and protecting methods and devices based on big data

A technology of business logic and learning method, applied in the field of protection methods and learning, business logic learning based on big data, and protection devices, which can solve problems such as waste in the authentication process, loopholes in business logic, and damage to customer experience.

Inactive Publication Date: 2018-10-19
CHINANETCENT TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Complex business logic often produces certain flaws, and flaws in business logic can lead to some loopholes
For example: when there is a loophole in the business logic of the order, the amount of the order can be modified at will, causing serious financial problems
[0003] Existing protection measures for business logic are usually multiple checks or manual review of business logic. However, these methods are often accompanied by a complicated certification process and waste a lot of manpower and material resources. The protection efficiency is not high and will damage the customer's reputation. Experience

Method used

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  • Service logic learning and protecting methods and devices based on big data
  • Service logic learning and protecting methods and devices based on big data
  • Service logic learning and protecting methods and devices based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0017] This application provides a business logic learning method based on big data, please refer to figure 1 , the method may include the following steps.

[0018] S11: Receive the network request sent by the requester, identify the current request identifier of the network request, and parse the process information of the network request.

[0019] In this implementation manner, the network request may be an HTTP request including a URL (Uniform Resource Locator, Uniform Resource Locator). For a large number of network requests, network requests can be classified according to the parameters carried in the network requests, and network requests of the same category can be formatted into formatted requests of the same parameter type. A large number of network requests can be formatted into different A formatted request for the parameter type. For example, the URL of the network request is http: / / www.xx.com / xx.php? a=1, http: / / www.xx.com / xx.php? a=2, where the parameters a=1...

Embodiment 2

[0043] see figure 2 , the present application also provides a big data-based business logic learning device, the device includes a memory and a processor, and a computer program is stored in the memory, and when the computer program is executed by the processor, the following steps are implemented:

[0044] receiving the network request sent by the requesting party, identifying the current request identifier of the network request and parsing the process information of the network request;

[0045] Extracting the reference request identifier from the flow information, and judging whether there is a direction from the reference request identifier to the current request identifier in the flow direction table, and updating the flow direction table based on the judgment result;

[0046] When responding to the network request, issue a tracking code for the network request, the tracking code includes the current request identifier and the timestamp when the tracking code is issued;...

Embodiment 3

[0051] Based on big data learning, after completing the business logic learning process, this application also provides a business logic protection method based on big data, please refer to image 3 , the method includes:

[0052] S21: Receive the network request sent by the requester, and identify the current request identifier of the network request.

[0053] In this embodiment, after a network request is received, the business logic of the network request may be judged. Specifically, first, the network request can be formatted into a formatted request of the corresponding parameter type. According to the learning method of the first embodiment above, each formatted request corresponds to a unique identifier, and then the format can be queried in the learning result Whether there is a corresponding unique identifier for the optimization request.

[0054] It should be noted that if the unique identifier of the formatting request corresponding to the network request cannot b...

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PUM

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Abstract

The invention discloses service logic learning and protecting methods and devices based on big data, wherein the learning method comprises: receiving a network request sent by a requesting party, identifying the current request identifier of the network request, and analyzing the process information of the network request; extracting a reference request identifier from the process information, anddetermining whether there is a direction, in a process direction table, that points from the reference request identifier to the current request identifier, and updating the process direction table based on a determined result; and issuing a tracking code for the network request, wherein the tracking code includes the current request identifier and a time stamp for issuing the tracking code. Thetechnical solution provided by the present application can improve the service logic protection efficiency based on big data, can adapt to various service logic scenarios, and can flexibly adapt to changes in various service logic requirements.

Description

technical field [0001] The invention relates to the field of Internet technology, in particular to a big data-based business logic learning and protection method and a learning and protection device. Background technique [0002] With the continuous development of the Internet and computer technology, the complexity of the business system is also increasing with the development of business requirements. The diversity of business will make the main business logic extend out of logical branches, and the business logic will become more and more complex. Complex business logic often produces certain flaws, and flaws in business logic can lead to some loopholes. For example: when there is a loophole in the business logic of the order, the amount of the order can be modified at will, causing serious financial problems. [0003] Existing protection measures for business logic are usually multiple checks or manual review of business logic. However, these methods are often accompani...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08H04L29/06
CPCH04L63/1441H04L67/62H04L63/1425G06F16/9566H04L2463/121G06F16/9017H04L63/0236H04L63/107H04L63/1433
Inventor 黄梅芬
Owner CHINANETCENT TECH