Anti-crawler method and system based on operation environment feature identification

An operating environment and feature recognition technology, which is applied in the fields of crawler recognition and anti-crawler, can solve the problems of information resource acquisition and theft, slow running speed of servers, etc., and achieve the effect of increasing difficulty, increasing possibility and reducing misjudgment rate

Active Publication Date: 2017-12-01
成都优易数据有限公司
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of the above-mentioned prior art, the purpose of the present invention is to provide an anti-crawler method and system based on operating environment feature recognition, so as to solve the problem of slow running speed of

Method used

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  • Anti-crawler method and system based on operation environment feature identification
  • Anti-crawler method and system based on operation environment feature identification

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Embodiment 1

[0072] Among them, such as figure 1 As shown, the server includes a data acquisition module, a data interface module 1 , a feature algorithm generation module 2 , a data storage module 3 , a data analysis module 4 and an access processing module 5 .

[0073] The functions of each functional module are introduced as follows:

[0074] Data acquisition module Data interface module 1 is used for sending and receiving data.

[0075] The feature algorithm generating module 2 is used to generate a function matrix, a selector feature code and a selector.

[0076] The data storage module 3 is used to store the selection code and function matrix running time data returned by the client under different feature settings.

[0077] The data analysis module 4 is used to analyze the data in the data storage module, and when receiving the function matrix running time data from the client, use the data to calculate the operating environment characteristic category to verify whether the server...

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Abstract

The invention discloses an anti-crawler method and system based on operation environment feature identification, and relates to the field of anti-crawler technology, and addresses the technical problems of crawler program identification and anti-crawling strategy implementation. The method herein includes the following steps: generating a new strategy packet and an option code which is for operating the new strategy packet, using the new strategy packet to update the current strategy packet of a server and establishing a feature type white list about the operation feature data of the new strategy packet; transmitting the option code to a client, then transmitting a response request to the client; the client, based on the option code, optionally operating the strategy packet for performing responding by the server, acquiring the feature data corresponding to the option code and returning the feature data to the server; analyzing the option code and the feature data corresponding to the option code, computing the feature type of the client and determining whether the feature type is on the feature type white list, and performing access control on the client which is not on the feature type white list.

Description

technical field [0001] The invention relates to the technical field of reptile identification and anti-reptile, in particular to an anti-reptile method and system based on operating environment feature recognition. Background technique [0002] With the advent of the era of big data, data becomes more and more important. To analyze valuable data from data, a large amount of data is first required. The data on the Internet has attracted the attention of enterprises and individuals due to its openness, massiveness and extensiveness. Many web crawlers have been developed and utilized to collect various data on the Internet. However, web crawlers can have many negative effects. The web crawler program will request a large number of servers in a short period of time, resulting in a decrease in server performance; some crawlers will maliciously collect a large amount of public data, aggregate and sell it, and infringe copyright. There are also some websites whose data has high...

Claims

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Application Information

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IPC IPC(8): H04L29/06
CPCH04L63/10H04L63/1441H04L63/20
Inventor 夏珺峥蒋平川
Owner 成都优易数据有限公司
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