Network anomaly detection
    1.
    发明授权

    公开(公告)号:US11861453B2

    公开(公告)日:2024-01-02

    申请号:US17979508

    申请日:2022-11-02

    申请人: GOOGLE LLC

    IPC分类号: G06N3/08 H04W24/08 H04W84/04

    CPC分类号: G06N3/08 H04W24/08 H04W84/042

    摘要: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

    Network Anomaly Detection
    2.
    发明申请

    公开(公告)号:US20210133574A1

    公开(公告)日:2021-05-06

    申请号:US17145236

    申请日:2021-01-08

    申请人: Google LLC

    IPC分类号: G06N3/08 H04W24/08

    摘要: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

    Network anomaly detection
    3.
    发明授权

    公开(公告)号:US10891546B2

    公开(公告)日:2021-01-12

    申请号:US16397082

    申请日:2019-04-29

    申请人: Google LLC

    IPC分类号: G06N3/08 H04W24/08 H04W84/04

    摘要: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

    Network anomaly detection
    4.
    发明授权

    公开(公告)号:US11507837B2

    公开(公告)日:2022-11-22

    申请号:US17145236

    申请日:2021-01-08

    申请人: Google LLC

    IPC分类号: G06N3/08 H04W24/08 H04W84/04

    摘要: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

    Network Anomaly Detection
    5.
    发明申请

    公开(公告)号:US20200342311A1

    公开(公告)日:2020-10-29

    申请号:US16397082

    申请日:2019-04-29

    申请人: Google LLC

    IPC分类号: G06N3/08 H04W24/08

    摘要: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.