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    GENERATING LONG-TERM NETWORK CHANGES FROM SLA VIOLATIONS
    32.
    发明申请
    GENERATING LONG-TERM NETWORK CHANGES FROM SLA VIOLATIONS 有权

    公开(公告)号：US20230027995A1

    公开(公告)日：2023-01-26

    申请号：US17381343

    申请日：2021-07-21

    Applicant: Cisco Technology, Inc.

    Inventor： David Tedaldi ,  Jean-Philippe VASSEUR ,  Grégory MERMOUD ,  Pierre-André SAVALLE ,  Vinay Kumar KOLAR

    IPC: H04W28/02 ,  H04L12/24

    Abstract: In one embodiment, a device obtains information regarding temporary routing patches applied to a network. Each temporary routing patch implements a routing change in the network for a specified amount of time to avoid or mitigate against a service level agreement violation. The device evaluates, using the information regarding the temporary routing patches applied to the network, a plurality of replay scenarios for the network. The device determines, based on the plurality of replay scenarios, a long-term configuration change for the network. The device provides an indication of the long-term configuration change for display.

    Compressed transmission of network data for networking machine learning systems
    33.
    发明授权
    Compressed transmission of network data for networking machine learning systems 有权

    公开(公告)号：US11438240B2

    公开(公告)日：2022-09-06

    申请号：US16808896

    申请日：2020-03-04

    Applicant: Cisco Technology, Inc.

    Inventor： Mukund Yelahanka Raghuprasad ,  David Tedaldi ,  Vinay Kumar Kolar ,  Jean-Philippe Vasseur

    IPC: H04L41/16 ,  G06N3/08 ,  H04L47/2441 ,  H04L41/5019 ,  G06K9/62

    Abstract: In one embodiment, a service receives telemetry data indicative of a plurality of performance metrics captured in a network. The service jointly trains, using the received telemetry data, a compression model and an inference model, the compression model being a first machine learning model trained to convert the telemetry data into a compressed representation of the telemetry data and the inference model being a second machine learning model trained to take the compressed representation of the telemetry data as input and apply a classification label to it. The service deploys the compression model to the network. The service receives compressed telemetry data generated by the compression model deployed to the network. The service uses the inference model to classify the compressed telemetry data generated by the compression model deployed to the network.

    PROTECTING DEVICE CLASSIFICATION SYSTEMS FROM ADVERSARIAL ENDPOINTS
    37.
    发明申请
    PROTECTING DEVICE CLASSIFICATION SYSTEMS FROM ADVERSARIAL ENDPOINTS 有权

    公开(公告)号：US20210297442A1

    公开(公告)日：2021-09-23

    申请号：US16823650

    申请日：2020-03-19

    Applicant: Cisco Technology, Inc.

    Inventor： Jean-Philippe Vasseur ,  Grégory Mermoud ,  Pierre-André Savalle ,  David Tedaldi

    IPC: H04L29/06

    Abstract: In various embodiments, a device classification service clusters devices in a network into a device type cluster based on attributes associated with the devices. The device classification service tracks changes to the device type cluster over time. The device classification service detects an attack on the device classification service by one or more of the devices based on the tracked changes to the device type cluster. The device classification service initiates a mitigation action for the detected attack on the device classification service.

    DETECTION AND RESOLUTION OF RULE CONFLICTS IN DEVICE CLASSIFICATION SYSTEMS
    39.
    发明申请
    DETECTION AND RESOLUTION OF RULE CONFLICTS IN DEVICE CLASSIFICATION SYSTEMS 审中-公开

    公开(公告)号：US20200382373A1

    公开(公告)日：2020-12-03

    申请号：US16428202

    申请日：2019-05-31

    Applicant: Cisco Technology, Inc.

    Inventor： Grégory Mermoud ,  Jean-Philippe Vasseur ,  Pierre-Andre Savalle ,  David Tedaldi

    IPC: H04L12/24 ,  H04L29/06 ,  H04L12/723

    Abstract: In one embodiment, a service receives a plurality of device type classification rules, each rule comprising a device type label and one or more device attributes used as criteria for application of the label to a device in a network. The service estimates, across a space of the device attributes, device densities of devices having device attributes at different points in that space. The service uses the estimated device densities to identify two or more of the device type classification rules as having overlapping device attributes. The service determines that the two or more device type classification rules are in conflict, based on the two or more rules having different device type labels. The service generates a rule conflict resolution that comprises one of the device type labels from the conflicting two or more device type classification rules.

    Using random forests to generate rules for causation analysis of network anomalies
    40.
    发明授权
    Using random forests to generate rules for causation analysis of network anomalies 有权

    公开(公告)号：US10771313B2

    公开(公告)日：2020-09-08

    申请号：US15881909

    申请日：2018-01-29

    Applicant: Cisco Technology, Inc.

    Inventor： David Tedaldi ,  Grégory Mermoud ,  Jean-Philippe Vasseur

    IPC: H04L12/24

    Abstract: In one embodiment, a network assurance service receives one or more sets of network characteristics of a network, each network characteristic forming a different feature dimension in a multi-dimensional feature space. The network assurance service applies machine learning-based anomaly detection to the one or more sets of network characteristics, to label each set of network characteristics as anomalous or non-anomalous. The network assurance service identifies, based on the labeled one or more sets of network characteristics, an anomaly pattern as a collection of unidimensional cutoffs in the feature space. The network assurance service initiates a change to the network based on the identified anomaly pattern.

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