MACHINE LEARNING BASED NETWORK ANOMALY DETECTION SYSTEM

    公开(公告)号:US20240244070A1

    公开(公告)日:2024-07-18

    申请号:US18130966

    申请日:2023-04-05

    Applicant: VMWARE, INC.

    CPC classification number: H04L63/1425 H04L41/16

    Abstract: The disclosure provides an approach for detecting anomalous behavior of network traffic within a network environment. Embodiments include receiving, by a risk analyzer operating on a server, network traffic flow records for one or more traffic flows in a network environment. Embodiments also include serializing flow entries within the network traffic flow records into a plurality of temporal buckets. Embodiments includes analyzing the network traffic flow records by a machine learning model configured to detect anomalous behavior based on (i) spatial patterns between at least a first set of features of flow entries and (ii) temporal patterns between the flow entries. Further embodiments include initiating a network action in response to detecting anomalous behavior in at least one of the network traffic flow records.

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