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Model generation method, abnormal flow detection method and device, electronic equipment and computer readable storage medium

A technology of model generation and anomaly detection, applied in the network field, can solve the problems that abnormal traffic detection methods are too macroscopic and easy to miss

Active Publication Date: 2019-09-06
BEIJING QIYI CENTURY SCI & TECH CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The invention provides a model generation method, an abnormal flow detection method, a device, an electronic device, and a computer-readable storage medium, so as to solve the problem that the existing abnormal flow detection method is too macroscopic and easy to miss detection

Method used

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  • Model generation method, abnormal flow detection method and device, electronic equipment and computer readable storage medium
  • Model generation method, abnormal flow detection method and device, electronic equipment and computer readable storage medium
  • Model generation method, abnormal flow detection method and device, electronic equipment and computer readable storage medium

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Embodiment Construction

[0091] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0092] figure 1 shows a flow chart of a model generation method provided by an embodiment of the present invention, such as figure 1 As indicated, the method may include:

[0093] Step 101, collect historical traffic data in multiple different time periods.

[0094] In the embodiment of the present invention, to generate a detection model, it is first necessary to collect historical traffic data in different time periods as training data.

[0095] S...

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Abstract

The invention provides a model generation method, an abnormal flow detection method and device, electronic equipment and a computer readable storage medium. The abnormal flow detection method comprises the following steps of acquiring to-be-detected flow data in a target time period, acquiring a to-be-detected proportion of at least one index, inputting the to-be-detected proportion into an abnormal detection model for detection to obtain a detection result, and finally judging whether the to-be-detected flow data in which the to-be-detected proportion is located is abnormal according to the detection result. In the embodiment of the invention, through obtaining a to-be-measured proportion of at least one index of to-be-measured flow data, the proportion components contained in the to-be-detected flow data are quantized, and whether the acquired to-be-detected proportion meets the rule of historical probability distribution and integral clustering or not is judged by the aid of the abnormal detection model, so that the to-be-detected flow data are comprehensively detected, and the accuracy and comprehensiveness of detection results are guaranteed.

Description

technical field [0001] The embodiments of the present invention relate to the field of network technology, and in particular, to a model generation method, an abnormal traffic detection method, a device, an electronic device, and a computer-readable storage medium. Background technique [0002] As Internet technology enters every aspect of people's lives, various websites and applications often organize various activities to interact with users, such as organizing users to collect coupons, draw prizes, votes and other activities. But at the same time, in order to cheat coupons or prizes, some hackers will use the brush tool to maliciously brush the amount. After the website or application is swiped, the background data will be inaccurate, and it will be impossible to know the user's participation in the activity. At the same time, it will also cause problems such as the inability of normal users to participate in the activity. [0003] In order to avoid the occurrence of th...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/2321G06F18/214
Inventor 宗志远
Owner BEIJING QIYI CENTURY SCI & TECH CO LTD
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