CDN traffic anomaly detection device and method based on improved hierarchical temporal memory network
A time memory and anomaly detection technology, applied in neural learning methods, biological neural network models, electrical components, etc., can solve the problems that cannot meet the response time requirements of large-traffic network links and diagnose abnormal types. To solve problems such as good solutions to improve performance, reduce the probability of false positives, and improve accuracy
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[0086] combine figure 1 , the present invention is a CDN traffic anomaly detection device based on an improved layered temporal memory network, comprising a data collection module, a data preprocessing module, a data storage module, a system scheduling module, an anomaly detection module and a display module;
[0087] Described data collection module, use distributed search engine ElasticSearch, log parsing tool Logstash, analysis and visualization platform Kbana to collect the original log of Nginx, use the log file that is installed on the server to monitor appointment and obtain change information;
[0088] The data preprocessing module is used for performing data analysis on the sub-fields of the original log, and aggregating the data of the parsed time and flow value fields according to the time granularity to obtain the CDN log flow time series;
[0089]The data storage module includes a distributed search engine Elasticsearch query database and a Mysql common database, ...
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