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Fraud webpage detection method, computer device and computer readable storage medium

A detection method and computer program technology, applied in the Internet field, can solve the problems of a large amount of manpower input, low recall rate, and low detection accuracy rate, and achieve the effects of saving labor costs, avoiding low recall rate, and high detection accuracy rate

Active Publication Date: 2017-09-05
北京如布科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method is limited by corpus, and it takes a long time for new fraud types or methods to collect rich corpus, and due to confrontation and other reasons, the original fraud method may be eliminated soon, and the recall rate is low
[0004] (2) Use the method of finding various key characteristic words and characteristic sentences in web pages. Although this method can be quickly developed when new fraudulent methods are discovered, maintaining these characteristic words and characteristic sentences requires a lot of manpower input, and the The detection accuracy of the method is low
[0005] For the above problems, no effective solutions have been proposed so far

Method used

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  • Fraud webpage detection method, computer device and computer readable storage medium
  • Fraud webpage detection method, computer device and computer readable storage medium
  • Fraud webpage detection method, computer device and computer readable storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0023] figure 1 It is a flow chart of the method for detecting fraudulent webpages provided by Embodiment 1 of the present invention. This embodiment is applicable to detecting fraudulent webpages, specifically, fraud detection may be performed on webpages requested by user terminals. The method can be executed by a device for detecting fraudulent webpages, preferably, it can be executed by a server. Such as figure 1 As shown, the fraudulent web page detection method of the present embodiment includes the following steps:

[0024] Step S110, acquiring account information of the current webpage.

[0025] In this step, the current webpage refers to the webpage requested by the user terminal from the server. Before sending or displaying the webpage to the user terminal, fraudulent detection of the webpage is required to improve the security of webpage browsing. Account information refers to the account corresponding to a unique user, because the owner of a fraudulent webpage ...

Embodiment 2

[0036] On the basis of the first embodiment above, this embodiment provides a process for establishing a blacklist. The establishment of the blacklist is performed before acquiring the account information of the current webpage, that is, before step S110. Such as figure 2 As shown, a blacklist can be established through the following steps:

[0037] Step S210, acquiring the sample webpage and the account information of each webpage in the sample webpage.

[0038] Wherein, the sample webpage is a batch of webpages used to obtain account information for building a blacklist. A large number of webpage resources can be obtained from the server or source station as sample webpages; fraudulent webpages detected by existing methods (such as the method described in the background technology) can also be obtained from servers, fraud reporting platforms or third-party fraud detection software as samples part of the web page. Specifically, the account information may be obtained by p...

Embodiment 3

[0054] Figure 4 It is a structural block diagram of a device for detecting fraudulent webpages provided by Embodiment 3 of the present invention. This embodiment is applicable to detection of fraudulent webpages, and the device can detect fraudulent webpages requested by a user terminal. Such as Figure 4 As shown, the device includes: an information acquisition module 41 , a first fraud detection module 42 , a second fraud detection module 43 and a fraud determination module 44 .

[0055] The information acquiring module 41 is configured to acquire the account information of the current webpage.

[0056] The first fraud detection module 42 is configured to perform fraud detection on the current webpage according to the account information and the preset blacklist, and obtain a first detection result.

[0057] The second fraud detection module 43 is configured to perform fraud detection on the current webpage according to preset characteristic information, and obtain a seco...

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Abstract

The embodiment of the invention discloses a fraud webpage detection method, a computer device and a computer readable storage medium. The method comprises the following steps: obtaining account information of a current webpage; performing fraud detection on the current webpage according to the account information and a preset blacklist to obtain a first detection result; performing fraud detection on the current webpage according to preset feature information to obtain a second detection result; and if both of the first detection result and the second detection result indicate that the current webpage is a suspected fraud webpage, determining that the current webpage is a fraud webpage. The fraud webpage detection method disclosed by the embodiment of the invention has nothing to do with the fraud type or fraud method, the corpus of new fraud types or fraud methods does not need to be collected, and the problem of a low recall rate resulting from that the fraud type or fraud method is eliminated is avoided; the preset blacklist and the preset feature information do not require a high labor cost for maintenance, thereby having little manual intervention and reducing the labor cost; and in addition, the fraud webpage is determined in combination with the detection results of the two fraud detection modes, therefore the detection accuracy is high.

Description

technical field [0001] The embodiment of the present invention relates to the technical field of the Internet, and in particular to a fraudulent webpage detection method, computer equipment and a computer-readable storage medium. Background technique [0002] At present, there are generally two methods for detecting whether a web page is a fraudulent web page: [0003] (1) Using the method of machine learning, classify the fraudulent webpages collected from various channels according to their fraudulent fields, and collect legitimate webpages as non-fraudulent webpages, and then obtain a classifier through training. When detecting, the classifier directly classifies the webpage to determine whether the webpage is a fraudulent webpage and its fraudulent type. However, this method is limited by the corpus, and it takes a long time for new fraud types or methods to collect rich corpus, and due to confrontation and other reasons, the original fraud methods may be eliminated soo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06H04L12/26
CPCH04L43/16H04L63/1416H04L63/1441
Inventor 李苗苗
Owner 北京如布科技有限公司