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    MACHINE LEARNING-BASED VNF ANOMALY DETECTION SYSTEM AND METHOD FOR VIRTUAL NETWORK MANAGEMENT
    1.
    发明申请
    MACHINE LEARNING-BASED VNF ANOMALY DETECTION SYSTEM AND METHOD FOR VIRTUAL NETWORK MANAGEMENT 有权

    公开(公告)号：US20220255817A1

    公开(公告)日：2022-08-11

    申请号：US17480070

    申请日：2021-09-20

    申请人： POSTECH Research and Business Development Foundation

    发明人： Won Ki HONG ,  Jae Hyoung YOO ,  Ji Bum HONG ,  Su Hyun PARK

    IPC分类号： H04L12/26 ,  H04L12/24 ,  G06F9/455 ,  G06N20/00

    摘要： A virtual network management-specific machine learning-based VNF anomaly detection system may comprise: a data collection unit configured to collect normal state data generated when a service is normally provided and abnormal state data generated through a fault injection method through a monitoring agent and a monitoring module in real time, store the collected data in a time-series database, and transmit the monitoring data to determine whether there is an abnormal state; and a data analysis unit configured to extract a feature necessary for detecting an abnormal state by pre-processing monitoring data received from the data collection unit and send data on the extracted data to an abnormal-state detection model so that the abnormal-state detection model analyzes data that is input in real time to determine whether there is an abnormal state and notifies a network manager when an abnormal state occurs.