System and method for managing data including identifying a data protection pool based on a data classification analysis

    公开(公告)号:US10943016B2

    公开(公告)日:2021-03-09

    申请号:US16177230

    申请日:2018-10-31

    Abstract: A system and method for managing data includes identifying, in response to a storage request from a tenant system, a first data protection pool based on a data classification analysis performed on data associated with the storage request and initiating storage of data associated with the storage request in a first storage system associated with the first data protection pool. A pattern matching model and data sampled from the tenant system may be used to identify data characteristics, which may include data type, data retention, data sensitivity, and data location. At least some data characteristics may be obtained using a plugin to a tenant system on which the data associated with the storage request is stored.

    METHOD FOR APPROXIMATING SIMILARITY BETWEEN OBJECTS

    公开(公告)号:US20190332492A1

    公开(公告)日:2019-10-31

    申请号:US15964527

    申请日:2018-04-27

    Inventor: Peter Marelas

    Abstract: Systems and methods for determining similarity between sets of objects are disclosed. A set of hashes are generated for a set of objects. A similarity vector is generated for the set of hashes. The similarity vector is a compact representation of the set of hashes and of the corresponding set of objects. The similarity of the set of objects is determined by comparing the similarity vector of the set of objects with other similarity vectors. In a data protection system, the set of objects can be placed with the node or system that stores objects that are most similar to the set of objects being placed.

    Vaulting data from a public cloud

    公开(公告)号:US11829325B2

    公开(公告)日:2023-11-28

    申请号:US17839110

    申请日:2022-06-13

    Inventor: Peter Marelas

    Abstract: Data moving micro-services are deployed to a public cloud and a cloud vault target (CVT). A first request is issued to the public cloud for a first snapshot of data belonging to a customer tenant. The first snapshot is accessed to write the data to a first cloud volume in the public cloud. Data of the first cloud volume is vaulted to the CVT via the micro-services. The first cloud volume is maintained in the public cloud. A second request is issued to the public cloud for a second snapshot of the data belonging to the customer tenant. The second snapshot is accessed to write the data to a second cloud volume in the public cloud. Data of the second cloud volume is compared against data of the first cloud volume to identify redundant data. Data of the second cloud volume that is not redundant is vaulted to the CVT.

    Automated agent for data copies verification

    公开(公告)号:US10664619B1

    公开(公告)日:2020-05-26

    申请号:US15877706

    申请日:2018-01-23

    Inventor: Peter Marelas

    Abstract: The implementation of an automated agent for data copy verification. Specifically, the implementation entails the execution of an intelligent, machine-learning based method and system for determining the integrity of data copies (i.e., for identifying whether data copies of a same data set have been impacted by malicious activities). Upon determining that data integrity is likely compromised, one or more corrective actions may be triggered. These actions may mitigate the spread of corruption and/or infection.

    Applying machine-learning to optimize the operational efficiency of data backup systems

    公开(公告)号:US11061780B1

    公开(公告)日:2021-07-13

    申请号:US16596353

    申请日:2019-10-08

    Abstract: Applying machine-learning to optimize the operational efficiency of data backup systems is described. A machine-learning system creates a training set of multiple features for each of multiple historical data backup jobs. The machine-learning system trains a prediction model to predict, based on the training set, the probabilities that the corresponding historical data backup jobs failed during the next historical data backup window. The machine-learning system creates an operational set of multiple features for each of multiple scheduled data backup jobs. The trained prediction model predicts, based on the operational set, the probabilities that the corresponding scheduled data backup jobs will fail during the next scheduled data backup window. The predicted probability that a scheduled data backup job will fail during the next scheduled data backup window is output, thereby enabling an operator to remediate the scheduled data backup job prior to the next scheduled data backup window.

    Input/output (I/O) inspection methods and systems to detect and defend against cybersecurity threats

    公开(公告)号:US10586052B1

    公开(公告)日:2020-03-10

    申请号:US15724814

    申请日:2017-10-04

    Inventor: Peter Marelas

    Abstract: Input/output (I/O) inspection methods and systems are disclosed to detect and defend against cybersecurity threats. In one example, a method includes intercepting input/output (I/O) operations including I/O write operations for a storage system. Segments of data related to the intercepted write I/O operations are stored in a write I/O buffer. One or more levels of inspection are performed on the segments of data stored in the write I/O buffer to detect a security threat. A protection instruction is injected in any segments of data having a detected security threat. The defensive action can be performed for the injected protection instruction prior to storing segments of data in the write I/O buffer in the storage system. The protection instruction can be injected at the head of the segments of data having a detected security threat.

    VAULTING DATA FROM A PUBLIC CLOUD

    公开(公告)号:US20220309031A1

    公开(公告)日:2022-09-29

    申请号:US17839110

    申请日:2022-06-13

    Inventor: Peter Marelas

    Abstract: Data moving micro-services are deployed to a public cloud and a cloud vault target (CVT). A first request is issued to the public cloud for a first snapshot of data belonging to a customer tenant. The first snapshot is accessed to write the data to a first cloud volume in the public cloud. Data of the first cloud volume is vaulted to the CVT via the micro-services. The first cloud volume is maintained in the public cloud. A second request is issued to the public cloud for a second snapshot of the data belonging to the customer tenant. The second snapshot is accessed to write the data to a second cloud volume in the public cloud. Data of the second cloud volume is compared against data of the first cloud volume to identify redundant data. Data of the second cloud volume that is not redundant is vaulted to the CVT.

    Automated agent for data copies verification

    公开(公告)号:US10659483B1

    公开(公告)日:2020-05-19

    申请号:US15799088

    申请日:2017-10-31

    Inventor: Peter Marelas

    Abstract: The implementation of an automated agent for data copies verification. Specifically, the implementation entails the execution of an intelligent, machine-learning based method and system for determining the integrity of data copies (i.e., for identifying whether data copies of a same data set have been impacted by malicious activities).

    FINE-GRAINED SHARED MULTI-TENANT DE-DUPLICATION SYSTEM

    公开(公告)号:US20190332597A1

    公开(公告)日:2019-10-31

    申请号:US16506896

    申请日:2019-07-09

    Inventor: Peter Marelas

    Abstract: In one example, a method includes receiving, at a cloud storage site, chunks that each take the form of a hash of a combination that includes two or more salts and a file object, and one of the salts is a retention salt shared by the chunks, monitoring a time period associated with the retention salt, when the time period has expired, removing the chunks that include the retention salt, and depositing the removed chunks in a deleted items cloud store.

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