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    Abnormal classic authorization detection systems
    2.
    发明授权
    Abnormal classic authorization detection systems 有权

    公开(公告)号：US12282546B2

    公开(公告)日：2025-04-22

    申请号：US17516183

    申请日：2021-11-01

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Idan Hen ,  Ilay Grossman ,  Avichai Ben David

    IPC: G06F21/55 ,  H04L9/40

    Abstract: A system to detect an abnormal classic authorizations, such as in a classic authorization system of a resource access management system, and take action is described. The system determines an anomaly score in from a model applied to a classic assignment event. An indicator score is determined from the classic assignment event applied to domain-based rules. The security action is taken based on a combination of the anomaly score and the indicator score.

    USER IMPACT POTENTIAL FOR SECURITY ALERT MANAGEMENT
    5.
    发明申请
    USER IMPACT POTENTIAL FOR SECURITY ALERT MANAGEMENT 有权

    公开(公告)号：US20210120014A1

    公开(公告)日：2021-04-22

    申请号：US16660359

    申请日：2019-10-22

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Itay Argoety ,  Jonathan Moshe Monsonego ,  Idan Hen ,  Payal Rani ,  Sridhar Periyasamy

    IPC: H04L29/06 ,  G06F21/57 ,  G06F21/55 ,  H04L12/24

    Abstract: Techniques for user impact potential based security alert management in computer systems are disclosed. One example technique includes receiving an alert indicating that a security rule has been violated by a user. The example technique can also include, in response to receiving the data representing the alert, determining an impact score of the user based on the profile of the user. The impact score represents a deviation of an assigned value to the profile of the user and a mean value of assigned values of profiles of all users in the organization. The example technique can further include calculating a ranking value of the alert in relation to other alerts based on the determine impact score and other impacts scores corresponding to the other alerts and selectively surfacing the alert to a system analyst based on the calculated ranking value in relation to other alerts.

    MACHINE LEARNING APPROACH FOR SOLVING THE COLD START PROBLEM IN STATEFUL MODELS
    6.
    发明公开
    MACHINE LEARNING APPROACH FOR SOLVING THE COLD START PROBLEM IN STATEFUL MODELS 审中-公开

    公开(公告)号：US20230403289A1

    公开(公告)日：2023-12-14

    申请号：US17806889

    申请日：2022-06-14

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： Andrey Karpovsky ,  Idan Hen

    IPC: H04L9/40 ,  H04L41/16 ,  G06N20/20

    CPC classification number: H04L63/1425 ,  H04L41/16 ,  G06N20/20

    Abstract: A computing system generates from received user input an initial profile. The initial profile specifies expected behavioral patterns of datasets that are to be received by the computing system. The computing system extracts from received datasets features that are indicative of behavioral patterns of the received datasets. The computing system provides the initial profile to first machine-learning models. The first machine-learning models have been trained using a subset of the received datasets. The first machine-learning models use the initial profile to determine if the behavioral patterns of the received datasets are anomalous. The computing system includes second machine-learning models that have been trained using a subset of the received datasets. The second machine-learning models train a second profile based on the extracted features to specify behavioral patterns of the received datasets that are learned by the second machine-learning model.

    ABNORMAL CLASSIC AUTHORIZATION DETECTION SYSTEMS
    8.
    发明申请
    ABNORMAL CLASSIC AUTHORIZATION DETECTION SYSTEMS 有权

    公开(公告)号：US20230132611A1

    公开(公告)日：2023-05-04

    申请号：US17516183

    申请日：2021-11-01

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Idan Hen ,  Ilay Grossman ,  Avichai Ben David

    IPC: G06F21/55

    Abstract: A system to detect an abnormal classic authorizations, such as in a classic authorization system of a resource access management system, and take action is described. The system determines an anomaly score in from a model applied to a classic assignment event. An indicator score is determined from the classic assignment event applied to domain-based rules. The security action is taken based on a combination of the anomaly score and the indicator score.

    Detect anomalous container deployment at a container orchestration service
    9.
    发明授权
    Detect anomalous container deployment at a container orchestration service 有权

    公开(公告)号：US12265616B2

    公开(公告)日：2025-04-01

    申请号：US17536995

    申请日：2021-11-29

    Applicant: Microsoft Technology Licensing, LLC.

    Inventor： Amit Magen Medina ,  Dotan Patrich ,  Josef Weizman ,  Idan Hen

    IPC: G06F21/56 ,  G06N7/01 ,  G06N20/00

    Abstract: A computing system is configured to detect a request for a deployment of a container at a container orchestration service. One or more datasets associated with the deployment of the container are collected, and a plurality of features associated with the deployment are extracted based on the one or more datasets. A probability score is then generated based on the plurality of features, using a machine-learning model trained on datasets associated with historical deployments of containers that have been performed via the container orchestration service. The probability score indicates a probability that the deployment of the container is anomalous compared to the historical deployments of containers. When the probability score is greater than a threshold, the deployment of the container is determined as anomalous.

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