A Method for Online Abnormal Discovery of Virtual Assets Based on Data Flow
A virtual asset and anomaly detection technology, applied in the Internet field, can solve problems such as low timeliness and lack of a framework for outlier detection technology based on data streams, so as to prevent user losses, quickly and effectively detect anomalies, and save The effect of memory space
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[0072] A method for online abnormal discovery of virtual assets based on data streams, the specific hardware information of the virtual asset management system is as follows:
[0073] Virtual asset data flow processing cluster: 2 nodes, the node configuration is 4-core CPU, 32G memory, Centos6.564 bit system;
[0074] Behavioral mode computing cluster: 5 nodes, the node configuration is 4-core CPU, 16G memory, Centos6.564 system;
[0075] Virtual asset operation log database: 1 node, the node configuration is 2-core CPU, 8G memory, 2TB hard disk, Centos6.564-bit operating system;
[0076] Behavior pattern library: 1 node, the node configuration is 2-core CPU, 8G memory, 2TB hard disk, and Centos6.564-bit operating system.
[0077] The above-mentioned hardware configuration environment can handle concurrent operations of 1W-level users. The virtual asset data flow processing cluster extracts data summaries from the continuously inflowing data in real time, stores the data sum...
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