Methods and systems for document classification using machine learning

    公开(公告)号:US10970595B2

    公开(公告)日:2021-04-06

    申请号:US16281501

    申请日:2019-02-21

    Applicant: NETAPP, INC.

    Abstract: Methods and systems for document classification are provided. One method includes generating by a processor, a plurality of topics using content of a plurality of electronic documents, where each topic includes a plurality of words associated with the plurality of electronic documents; reducing by the processor, the plurality of topics to a subset of topics to represent the plurality of electronic documents based on a parameter indicating a property of each subset topic and separation between the subset topics; automatically generating by the processor, a tag for each subset topic, based on the tag's position within the subset topic; wherein each tag is an attribute of each subset topic; storing by the processor, the subset of topics with corresponding tags in a model data structure; and updating the model data structure by the processor based on one of a new topic and a new tag associated with an electronic document.

    SYSTEMS AND METHODS FOR DETECTING MALWARE ATTACKS

    公开(公告)号:US20240022597A1

    公开(公告)日:2024-01-18

    申请号:US18477879

    申请日:2023-09-29

    Applicant: NetApp Inc.

    CPC classification number: H04L63/145 H04L63/1416 G06F21/602

    Abstract: A method, a computing device, and a non-transitory machine-readable medium for detecting malware attacks. In one example, an agent implemented in an operating system detects an overwrite in which an original data component is overwritten with a new data component. The agent computes a plurality of features associated with the overwrite, the plurality of features including an original entropy corresponding to the original data component, a new entropy corresponding to the new data component, an overwrite fraction, and a set of divergence features. The agent determines whether the new data component is encrypted using the plurality of features.

    Systems and methods for detecting malware attacks

    公开(公告)号:US11792223B2

    公开(公告)日:2023-10-17

    申请号:US17062732

    申请日:2020-10-05

    Applicant: NetApp, Inc.

    CPC classification number: H04L63/145 G06F21/602 H04L63/1416

    Abstract: A method, a computing device, and a non-transitory machine-readable medium for detecting malware attacks. In one example, an agent implemented in an operating system detects an overwrite in which an original data component is overwritten with a new data component. The agent computes a plurality of features associated with the overwrite, the plurality of features including an original entropy corresponding to the original data component, a new entropy corresponding to the new data component, an overwrite fraction, and a set of divergence features. The agent determines whether the new data component is encrypted using the plurality of features.

    Systems and methods for protecting against malware attacks

    公开(公告)号:US11475132B2

    公开(公告)日:2022-10-18

    申请号:US16942123

    申请日:2020-07-29

    Applicant: NetApp, Inc.

    Abstract: A method, computing device, and non-transitory machine-readable medium for detecting malware attacks and mitigating data loss. In various embodiments, an agent is implemented in the operating system of a storage node to provide protection at the bottommost level in a data write path. The agent intercepts write requests and observes file events over time to detect anomalous behavior. For example, the agent may monitor incoming write requests and, when an incoming write request is detected, determine whether the file is associated with a malware attack risk based on an analysis of an encryption state of data in the file. If the file is associated with a malware attack risk, an entry for the file is added to a file log. The agent may analyze the chi-square values for data written to the files, the file log, and the file format to determine whether a malware attack is underway.

    AGGREGATE INLINE DEDUPLICATION WITH VOLUME GRANULAR ENCRYPTION

    公开(公告)号:US20220171557A1

    公开(公告)日:2022-06-02

    申请号:US17676342

    申请日:2022-02-21

    Applicant: NetApp Inc.

    Abstract: Techniques are provided for aggregate inline deduplication and volume granularity encryption. For example, data that is exclusive to a volume of a tenant is encrypted using an exclusive encryption key accessible to the tenant. The exclusive encryption key of that tenant is inaccessible to other tenants. Shared data that has been deduplicated and shared between the volume and another volume of a different tenant is encrypted using a shared encryption key of the volume. The shared encryption key is made available to other tenants. In this way, data can be deduplicated across multiple volumes of different tenants of a storage environment, while maintaining security and data privacy at a volume level.

    SYSTEMS AND METHODS FOR PROTECTING AGAINST MALWARE ATTACKS

    公开(公告)号:US20210334374A1

    公开(公告)日:2021-10-28

    申请号:US16942123

    申请日:2020-07-29

    Applicant: NetApp, Inc.

    Abstract: A method, a computing device, and a non-transitory machine-readable medium for detecting malware attacks (e.g., ransomware attacks) and mitigating data loss. In one or more embodiments, an agent is implemented in the operating system of a storage node to provide protection at the bottommost level in a data write path. The agent intercepts write requests and observes file events over time to detect anomalous behavior. For example, the agent may monitor incoming write requests and, when an incoming write request is detected, determine whether the file is associated with a malware attack risk based on an analysis of an encryption state of data in the file. If the file associated with a malware attack risk, an entry for the file is added to a file log. The agent may analyze the chi-square values for data written to the files, the file log, and the file format to determine whether a malware attack is underway.

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