ACTIONABILITY DETERMINATION FOR SUSPICIOUS NETWORK EVENTS

    公开(公告)号:US20210194896A1

    公开(公告)日:2021-06-24

    申请号:US16725819

    申请日:2019-12-23

    Abstract: Techniques are disclosed relating to reporting for network events within a computer network. A computer system may access a set of data corresponding to a particular network event within a computer network, where the set of data includes captured attributes of the particular network event. The computer system may then calculate, using the set of data, a security score indicative of suspiciousness of the event and an actionability score that is based on an extent to which of a particular group of attributes are missing from the set of data. The computer system may determine, based on the two scores, a combined score for the event. The computer system may then report a notification for the event, based on the combined score. Such techniques may decrease a number of reported events for a network, which may advantageously allow resources to be focused on a smaller set of events.

    Actionability determination for suspicious network events

    公开(公告)号:US11637841B2

    公开(公告)日:2023-04-25

    申请号:US16725819

    申请日:2019-12-23

    Abstract: Techniques are disclosed relating to reporting for network events within a computer network. A computer system may access a set of data corresponding to a particular network event within a computer network, where the set of data includes captured attributes of the particular network event. The computer system may then calculate, using the set of data, a security score indicative of suspiciousness of the event and an actionability score that is based on an extent to which of a particular group of attributes are missing from the set of data. The computer system may determine, based on the two scores, a combined score for the event. The computer system may then report a notification for the event, based on the combined score. Such techniques may decrease a number of reported events for a network, which may advantageously allow resources to be focused on a smaller set of events.

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