PRIVACY PRESERVING PERSON REIDENTIFICATION
    1.
    发明公开

    公开(公告)号:US20240290098A1

    公开(公告)日:2024-08-29

    申请号:US18113175

    申请日:2023-02-23

    CPC classification number: G06V20/48 G06V10/462 G06V10/757

    Abstract: In one embodiment, a device represents each of a plurality of objects depicted in video data captured by a plurality of cameras over time as a set of key points associated with that object. The device forms, for each of the plurality of objects, a set of timeseries of the set of key points associated with that object. The device performs reidentification of a particular one of the plurality of objects across video data captured by two or more of the plurality of cameras by matching sets of timeseries of key points associated with that object derived from video data captured by two or more of the plurality of cameras. The device provides an indication of the reidentification for display to a user.

    COGNITIVE AUTOMATION FOR NETWORKING, SECURITY, IoT, AND COLLABORATION

    公开(公告)号:US20210279615A1

    公开(公告)日:2021-09-09

    申请号:US17173380

    申请日:2021-02-11

    Abstract: In one embodiment, a device maintains a metamodel that describes a monitored system. The metamodel comprises a plurality of layers ranging from a sub-symbolic space to a symbolic space. The device tracks updates to the metamodel over time. The device updates the metamodel based in part on sub-symbolic time series data generated by the monitored system. The device receives, from a learning agent, a request for the updates to a particular layer of the metamodel associated with a specified time period. The device provides, to the learning agent, data indicative of one or more updates to the particular layer of the metamodel associated with the specified time period.

    Vulnerability analysis and segmentation of bring-your-own IoT devices

    公开(公告)号:US10742678B2

    公开(公告)日:2020-08-11

    申请号:US15891749

    申请日:2018-02-08

    Abstract: In one embodiment, a security device maintains a plurality of security enclaves for a computer network, each associated with a given level of security policies. After detecting a given device joining the computer network, the security device places the given device in a strictest security enclave of the plurality of security enclaves in response to joining the computer network. The security device then subjects the given device to joint adversarial training, where a control agent representing behavior of the given device is trained against an inciting agent, and where the inciting agent attempts to force the control agent to misbehave by applying destabilizing policies. Accordingly, the security device may determine control agent behavior during the joint adversarial training, and promotes the given device to a less strict security enclave of the plurality of enclaves in response to the control agent being robust against the attempts by the inciting agent.

    AUTOMATIC ONTOLOGY GENERATION FOR INTERNET OF THINGS APPLICATIONS

    公开(公告)号:US20200218751A1

    公开(公告)日:2020-07-09

    申请号:US16819783

    申请日:2020-03-16

    Abstract: A method comprises collecting, by a computing device located at an edge of a network, data items corresponding to information transmitted by endpoints using the network, generating, by the computing device, a probabilistic hierarchy using the data items, generating, by the computing device using the probabilistic hierarchy and natural language data, a similarity metric, generating, by the computing device using the probabilistic hierarchy, the natural language data, and the similarity metric, an ontology, detecting, by the computing device using the ontology, an anomaly, and in response to detecting the anomaly, sending a notification.

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