Adaptive real-time video data anti-cheating method and apparatus

Abstract

The embodiment of the invention provides an adaptive real-time video data anti-cheating method and apparatus. The method comprises: an IP address of real-time video data and a plurality of corresponding playing users are obtained; the IP address is obtained, and a first risk probability and a second risk probability are generated adaptively according to a video playing frequency value at the IP address within a first preset time period and a video playing frequency value of each of a plurality of playing users within the first preset time period; whether the first risk probability exceeds a first preset threshold value is determined to determine whether the IP address is a cheating IP address and whether the second risk probability exceeds a second preset threshold value is determined to determine whether the user is a cheating user; and then the cheating IP address and the cheating user are added into a black list base and the real-time video data of the cheating IP or cheating user are filtered. Therefore, the degree of identifying whether the real-time data are cheating data can be improved; the large-IP multi-user wrong determination possibility can be reduced; and re cheating of a high-risk playing user can be prevented.

Description

technical field [0001] The invention relates to the technical field of communication networks, in particular to an anti-cheating method and device for adaptive real-time video data. Background technique [0002] Watching videos has become the most important part of Chinese netizens' online entertainment life. All kinds of content such as dramas, variety shows, and movies have gained traffic and topic effects on the Internet. But at the same time, some companies or individuals use cheating methods to increase the number of clicks on a certain video, trying to use the method of "falsifying the number" to achieve the purpose of creating falsely high popularity. [0003] Since real-time data will complete log collection, transmission, anti-cheating, calculation, and storage in a short period of time, it is necessary to identify cheating data and normal data in a timely and accurate manner. The existing real-time video data anti-cheating method is generally a threshold limit met...

AI Technical Summary

Problems solved by technology

[0004] But, even under normal circumstances, there is also a huge difference in the number of clicks during the peak period of video data playback and the trough period of playback; will generate a lot of clicks

If the existing threshold limit algorithm is used, it may be misjudged as cheating data during the peak playback period or the normal data of the big IP outlet, and may be misjudged as the normal data during the low playback period or the cheating data of the small IP outlet

[0005] Therefore, the existing anti-cheating method for real-time video data has a low degree of identifying whether the real-time data is cheating data, which leads to misjudgment easily in the anti-cheating method for real-time video data

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