Anomaly detection for micro-service communications

    公开(公告)号:US10484410B2

    公开(公告)日:2019-11-19

    申请号:US15653689

    申请日:2017-07-19

    Abstract: Presented herein are techniques for detecting anomalies in micro-service communications that are indicative of security issues/problems for the application. More specifically, a computing device receives a plurality of micro-service communication records each associated with traffic sent between pairs of executables (nodes) that are related to a micro-services application. Each of the micro-service communication records includes a time series entry and an associated trace sequence identifier and each of the micro-service communication records are generated during a time period. The computing device analyzes the plurality of micro-service communications to detect possible anomalous communication patterns associated with the micro-services application during the time period.

    Methods and systems for counting people

    公开(公告)号:US10769531B2

    公开(公告)日:2020-09-08

    申请号:US15163833

    申请日:2016-05-25

    Abstract: Various systems and methods for counting people. For example, one method involves receiving input data at an analytics system that includes a neural network. The input data includes a representation of an environment, including representations of several people. The method also includes identifying the representations of the people in the representation of the environment. The method also includes updating an output value that indicates the number of people identified as being present in the environment.

    Methods and Systems for Counting People
    5.
    发明申请
    Methods and Systems for Counting People 审中-公开
    计数人的方法和系统

    公开(公告)号:US20160358074A1

    公开(公告)日:2016-12-08

    申请号:US15163833

    申请日:2016-05-25

    CPC classification number: G06N3/088 G06N3/0454

    Abstract: Various systems and methods for counting people. For example, one method involves receiving input data at an analytics system that includes a neural network. The input data includes a representation of an environment, including representations of several people. The method also includes identifying the representations of the people in the representation of the environment. The method also includes updating an output value that indicates the number of people identified as being present in the environment.

    Abstract translation: 各种系统和方法来计数人。 例如,一种方法涉及在包括神经网络的分析系统处接收输入数据。 输入数据包括环境的表示,包括几个人的表示。 该方法还包括识别人们在环境表现中的表示。 该方法还包括更新指示被识别为存在于环境中的人数的输出值。

    SPATIO-TEMPORAL EVENT WEIGHT ESTIMATION FOR NETWORK-LEVEL AND TOPOLOGY-LEVEL REPRESENTATIONS

    公开(公告)号:US20220086050A1

    公开(公告)日:2022-03-17

    申请号:US17079728

    申请日:2020-10-26

    Abstract: Presented herein are techniques to analyze network anomaly signals based on both a spatial component and a temporal component. A method includes identifying a plurality of factors that trigger a first anomaly signal by a first network node and a second anomaly signal by a second network node in a network comprising a plurality of network nodes, determining that the first network node is adjacent to the second network node in the plurality of network nodes, calculating an anomaly severity score for the first network node based on a number of co-occurring factors from among the plurality of factors that trigger both the first anomaly signal and the second anomaly signal, and adjusting the anomaly severity score for the first network node based on a value of a prior anomaly severity score for the first network node.

    Deep fusion reasoning engine (DFRE) for dynamic and explainable wireless network QoE metrics

    公开(公告)号:US10887197B2

    公开(公告)日:2021-01-05

    申请号:US16365096

    申请日:2019-03-26

    Abstract: In one embodiment, a network quality assessment service that monitors a network obtains multimodal data indicative of a plurality of measurements from the network and subjective perceptions of the network by users of the network. The network quality assessment service uses the obtained multimodal data as input to one or more neural network-based models. The network quality assessment service maps, using a conceptual space, outputs of the one or more neural network-based models to symbols. The network quality assessment service applies a symbolic reasoning engine to the symbols, to generate a conclusion regarding the monitored network. The network quality assessment service provides an indication of the conclusion to a user interface.

    DEEP FUSION REASONING ENGINE (DFRE) FOR DYNAMIC AND EXPLAINABLE WIRELESS NETWORK QoE METRICS

    公开(公告)号:US20210152440A1

    公开(公告)日:2021-05-20

    申请号:US17130804

    申请日:2020-12-22

    Abstract: In one embodiment, a network quality assessment service that monitors a network obtains multimodal data indicative of a plurality of measurements from the network and subjective perceptions of the network by users of the network. The network quality assessment service uses the obtained multimodal data as input to one or more neural network-based models. The network quality assessment service maps, using a conceptual space, outputs of the one or more neural network-based models to symbols. The network quality assessment service applies a symbolic reasoning engine to the symbols, to generate a conclusion regarding the monitored network. The network quality assessment service provides an indication of the conclusion to a user interface.

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