Data Encryption in a Distributed System
    11.
    发明申请

    公开(公告)号:US20190182039A1

    公开(公告)日:2019-06-13

    申请号:US16278551

    申请日:2019-02-18

    Abstract: A processor-based method for secret sharing in a computing system is provided. The method includes encrypting shares of a new secret, using a previous secret and distributing unencrypted shares of the new secret and the encrypted shares of the new secret, to members of the computing system. The method includes decrypting at least a subset of the encrypted shares of the new secret, using the previous secret and regenerating the new secret from at least a subset of a combination of the unencrypted shares of the new secret and the decrypted shares of the new secret.

    Resharing of a split secret
    12.
    发明授权

    公开(公告)号:US10211983B2

    公开(公告)日:2019-02-19

    申请号:US15668529

    申请日:2017-08-03

    Abstract: A processor-based method for secret sharing in a computing system is provided. The method includes encrypting shares of a new secret, using a previous secret and distributing unencrypted shares of the new secret and the encrypted shares of the new secret, to members of the computing system. The method includes decrypting at least a subset of the encrypted shares of the new secret, using the previous secret and regenerating the new secret from at least a subset of a combination of the unencrypted shares of the new secret and the decrypted shares of the new secret.

    MACHINE LEARNING MODEL FOR STORAGE SYSTEM

    公开(公告)号:US20230039564A1

    公开(公告)日:2023-02-09

    申请号:US17947975

    申请日:2022-09-19

    Abstract: Data associated with storage media utilized by one or more storage systems is received. The data is provided as an input to a machine learning model executed by a processing device. The machine learning model identifies one or more deterministic characteristics from the data. The one or more deterministic characteristics associated with the storage media are received from the machine learning model. A data structure comprising the one or more deterministic characteristics is generated for use in a telemetry process to qualify types of storage media.

    READABLE DATA DETERMINATION
    18.
    发明申请

    公开(公告)号:US20220138035A1

    公开(公告)日:2022-05-05

    申请号:US17570337

    申请日:2022-01-06

    Abstract: Data associated with a write request is stored at a storage device of multiple solid-state storage devices. A determination as to whether the data stored at the storage device is readable is made by determining whether a number of subsequent programming operations have been performed since the data was stored at the storage device. A notification that the stored data is readable from the storage device is generated upon determining that the data is readable.

    UTILIZING MACHINE LEARNING TO STREAMLINE TELEMETRY PROCESSING OF STORAGE MEDIA

    公开(公告)号:US20210334253A1

    公开(公告)日:2021-10-28

    申请号:US16857388

    申请日:2020-04-24

    Abstract: Data associated with storage media utilized by one or more storage systems is received. The data is provided as an input to a machine learning model executed by a processing device. The machine learning model identifies one or more deterministic characteristics from the data. The one or more deterministic characteristics associated with the storage media are received from the machine learning model. A data structure comprising the one or more deterministic characteristics is generated for use in a telemetry process to qualify types of storage media.

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