CDN flow anomaly detection device and method based on improved hierarchical time memory network

Abstract

The invention discloses a CDN flow anomaly detection device and method based on an improved hierarchical time memory network. The device comprises a data acquisition module, a data preprocessing module, a data storage module, a system scheduling module, an anomaly detection module and a display module. The method comprises the steps that a data collection module collects data of a native log, converts the data into a json format and sends the data to a data preprocessing module; feature extraction is carried out to obtain CDN flow time sequence representation, and the log data of the data acquisition module and the CDN data of the data preprocessing module are stored by the data storage module; the anomaly detection module acquires flow time series data through the system scheduling module, inputs the flow time series data into the time series anomaly detection model based on the improved hierarchical time memory network for online learning, completes anomaly possibility calculation and outputs a detection result of anomaly possibility judgment, and the display module visually displays a key process. The method has the advantages of high detection speed and high accuracy.

Description

technical field [0001] The invention relates to the technical field of CDN traffic anomaly detection, in particular to a CDN traffic anomaly detection device and method based on an improved layered temporal memory network. Background technique [0002] In recent years, with the continuous improvement of Internet infrastructure, the digital strategy has been systematically explained, Internet services have continued to penetrate, and the number of Internet users has maintained a steady growth. In order to reduce the pressure on the network due to the rapid growth of user groups and huge data transmission volume, Content Delivery Network (CDN) came into being. CDN can serve the Internet in different locations through large-scale distributed deployment of server infrastructure. The inherent distribution of CDN brings popular applications and hot content as close as possible to users, which greatly reduces network delays, improves users' access speed and quality of experience, ...

AI Technical Summary

Problems solved by technology

[0004] 1. The execution efficiency needs to be further improved, and at the same time, it cannot meet the response time requirements for abnormal detection of large-traffic network links;

[0005] 2. In the detection algorithm, it is very dependent on the determination of the detection threshold, how to accurately calculate the threshold cannot give a good solution;

[0006] 3. The traditional method focuses on finding abnormalities, and has little involvement in diagnosing abnormal types

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