DEVICE SPECIFIC MULTIPARTY COMPUTATION
    1.
    发明公开

    公开(公告)号:US20230143175A1

    公开(公告)日:2023-05-11

    申请号:US17514755

    申请日:2021-10-29

    CPC classification number: H04L9/085 G06F17/18 H04L9/0875 H04L2209/46

    Abstract: In one implementation, the disclosure provides systems and methods for a multi-party secret sharing protocol that is device specific in that the secret matrix used herein is tied to individual computing devices. Specifically, the method includes determining device channel errors of a plurality of computing devices based on channel impulse response (CIR) of communication channels of the plurality of computing devices, training a linear regression model using the device channel errors to generate learning with error (LWE) secrets for each of the plurality of computing devices, generating a general access structure secret matrix using the LWE secrets from each of the plurality of computing devices, and distributing shares of the general access structure secret matrix to the plurality of computing devices based on a multi-party secret sharing protocol, wherein the multi-party secret sharing protocol provides that the general access structure secret matrix cannot be constructed without shares from an authorized set of the computing devices.

    MOVING TARGET AUTHENTICATION PROTOCOLS

    公开(公告)号:US20220014386A1

    公开(公告)日:2022-01-13

    申请号:US16912482

    申请日:2020-06-25

    Abstract: In one implementation, the disclosure provides systems and methods for generating a secure signature using a device-specific and group-specific moving target authentication protocol. According to one implementation, generating the secure signature entails determining a state of a first device in association with a select time interval. The state of the first device is defined by one or more time-variable characteristics of the first device. The device computes an output for a signing function that depends upon the determined state of the first device associated with the first time interval.

    DATACENTER SERVICE FLOW OPTIMIZATION
    3.
    发明申请

    公开(公告)号:US20180375741A1

    公开(公告)日:2018-12-27

    申请号:US15632799

    申请日:2017-06-26

    Abstract: Systems and methods for improving efficiency in performing service actions for one or more storage systems are described. In one embodiment, the systems and methods include detecting a service event on at least one of one or more storage systems based at least in part on monitoring events on the one or more storage systems, creating a service action based at least in part on detecting the service event, adding the service action to a list of pending service actions associated with the one or more storage systems, and assigning one or more service actions from the list of pending service actions to a service window. In some cases, each service event in the list of pending service events represents an adverse condition awaiting repair in relation to at least one of the one or more storage systems.

    SELF-LEARNING EVENT RESPONSE ENGINE OF SYSTEMS

    公开(公告)号:US20180260268A1

    公开(公告)日:2018-09-13

    申请号:US15454252

    申请日:2017-03-09

    CPC classification number: G06F11/0727 G06F11/0781 G06F11/079 G06F11/0793

    Abstract: Systems and methods for a self-learning event response engine of systems are described. In one embodiment, the systems and methods may include identifying two or more patterns of events among a plurality of detected events stored in a database, identifying an adverse condition of the storage system that occurs as a result of a particular pattern of events from the identified patterns of events, identifying a corrective action that resolves the adverse condition of the storage system, detecting an occurrence of one or more events from the particular pattern of events, and implementing the corrective action based at least in part on detecting the occurrence of the one or more events from the particular pattern of events.

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