Search Patents
  • EDGE-BASED MACHINE LEARNING FOR ENCODING LEGITIMATE SCANNING
    Publication number: 20170279833
    Abstract: In one embodiment, a device in a network receives an indication that a network anomaly detected by an anomaly detector of a first node in the network is associated with scanning activity in the network. The device receives labeled traffic data associated with the detected anomaly that identifies whether the traffic data is associated with legitimate or illegitimate scanning activity. The device trains a machine learning-based classifier using the labeled traffic data to distinguish between legitimate and illegitimate scanning activity in the network. The device deploys the trained classifier to the first node, to distinguish between legitimate and illegitimate scanning activity in the network.
    Type: Application
    Filed: July 8, 2016
    Publication date: September 28, 2017
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle, Alexandre Honoré
  • ESTIMATING THE EFFICACY OF PREDICTIVE ROUTING FOR PROSPECTIVE DEPLOYMENTS
    Publication number: 20220385569
    Abstract: In one embodiment, a device obtains metadata for routing decisions made by a predictive routing service for a plurality of network deployments. The device identifies a network topology for a network deployment that does not use the predictive routing service. The device estimates, based on the metadata for routing decisions made by the predictive routing service, performance metrics for the predictive routing service were it to be used to make routing decisions for the network topology. The device sends, to a user interface, report data indicative of the performance metrics estimated for the predictive routing service were it to be used to make routing decisions for the network topology.
    Type: Application
    Filed: May 27, 2021
    Publication date: December 1, 2022
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle
  • PREDICTIVE ROUTING-BASED POLICY ADJUSTMENTS IN SOFTWARE-DEFINED NETWORKS
    Publication number: 20220286388
    Abstract: In one embodiment, a device obtains routing forecasts for a software defined network. The device splits a particular routing policy for the software defined network into two or more routing policies, based on the routing forecasts. The device makes an evaluation as to whether the two or more routing policies should be reverted back into the particular routing policy. The device sends, to a user interface, data indicative of the particular routing policy that was split into the two or more routing policies and the evaluation as to whether the two or more routing policies should be reverted back into the particular routing policy.
    Type: Application
    Filed: March 3, 2021
    Publication date: September 8, 2022
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle, Vinay Kumar Kolar
  • Root-causing user experience anomalies to coordinate reactive policies in application-aware routing
    Patent number: 11706130
    Abstract: In one embodiment, a device obtains user experience metrics for a plurality of sessions with an online application. The device detects a plurality of anomalies from among the user experience metrics. The device determines, based on a correlation between the plurality of anomalies, that a particular path entity is a root cause of the plurality of anomalies. The particular path entity comprises an egress service provider or data center of the online application. The device provides an indication of the particular path entity being the root cause of the plurality of anomalies.
    Type: Grant
    Filed: July 19, 2021
    Date of Patent: July 18, 2023
    Assignee: Cisco Technology, Inc.
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle
  • ELASTIC ALLOCATION OF RESOURCES FOR OPTIMIZING EFFICIENCY OF PREDICTIVE ROUTING SYSTEMS
    Publication number: 20230128567
    Abstract: In one embodiment, a device computes an efficiency metric regarding ingestion of telemetry data from a particular portion of a network by a predictive routing engine used to make predictive routing decisions for that portion of the network. The device makes a comparison between the efficiency metric and one or more control rules. The device determines, based on the comparison, whether ingestion of the telemetry data from the particular portion of the network by the predictive routing engine should be disabled. The device causes the predictive routing engine to stop ingesting telemetry data from the particular portion of the network.
    Type: Application
    Filed: October 21, 2021
    Publication date: April 27, 2023
    Inventors: Grégory Mermoud, Jean-Philippe VASSEUR, Vinay Kumar KOLAR, Pierre-André SAVALLE
  • Self organizing learning topologies
    Patent number: 10404727
    Abstract: In one embodiment, a networking device at an edge of a network generates a first set of feature vectors using information regarding one or more characteristics of host devices in the network. The networking device forms the host devices into device clusters dynamically based on the first set of feature vectors. The networking device generates a second set of feature vectors using information regarding traffic associated with the device clusters. The networking device models interactions between the device clusters using a plurality of anomaly detection models that are based on the second set of feature vectors.
    Type: Grant
    Filed: June 8, 2016
    Date of Patent: September 3, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Sébastien Gay, Grégory Mermoud, Pierre-André Savalle, Alexandre Honoré, Fabien Flacher
  • Continuous validation of active labeling for device type classification
    Patent number: 11297079
    Abstract: In one embodiment, a device classification service forms a device cluster by applying clustering to telemetry data associated with a plurality of devices. The service obtains device type labels for the device cluster. The service generates a device type classification rule using the device type labels and the telemetry data. The service determines whether the device type classification rule should be revalidated by applying a revalidation policy to the device type classification rule. The service revalidates the device type classification rule, based on a determination that the device type classification rule should be revalidated.
    Type: Grant
    Filed: May 6, 2019
    Date of Patent: April 5, 2022
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Pierre-Andre Savalle, Grégory Mermoud, David Tedaldi
  • ADAPTIVE STRESS TESTING OF SD-WAN TUNNELS FOR WHAT-IF SCENARIO MODEL TRAINING
    Publication number: 20220360502
    Abstract: In one embodiment, a service in a network computes an expected information gain associated with rerouting traffic from a first tunnel onto a backup tunnel in the network. The service initiates, based on the expected information gain, rerouting of the traffic from the first tunnel onto the backup tunnel. The service obtains performance measurements for the traffic rerouted onto the backup tunnel. The service uses the performance measurements to train a machine learning model to predict whether rerouting traffic from the first tunnel onto the backup tunnel will satisfy a service level agreement (SLA) of the traffic.
    Type: Application
    Filed: July 26, 2022
    Publication date: November 10, 2022
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle, Vinay Kumar Kolar
  • Self organizing learning topologies
    Patent number: 11240259
    Abstract: In one embodiment, a networking device at an edge of a network generates a first set of feature vectors using information regarding one or more characteristics of host devices in the network. The networking device forms the host devices into device clusters dynamically based on the first set of feature vectors. The networking device generates a second set of feature vectors using information regarding traffic associated with the device clusters. The networking device models interactions between the device clusters using a plurality of anomaly detection models that are based on the second set of feature vectors.
    Type: Grant
    Filed: July 11, 2019
    Date of Patent: February 1, 2022
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Sébastien Gay, Grégory Mermoud, Pierre-André Savalle, Alexandre Honoré, Fabien Flacher
  • INTERPRETABLE PEER GROUPING FOR COMPARING KPIs ACROSS NETWORK ENTITIES
    Publication number: 20210158260
    Abstract: In one embodiment, a network assurance service that monitors a network receives key performance indicators (KPIs) for a plurality of network entities in the network. The service applies clustering to the KPIs, to form KPI clusters. The service designates the network entities associated with the particular KPI cluster as belonging to a peer group, based in part on an assessment that the network entities associated with the particular KPI cluster share one or more attributes. The service uses a machine learning model to identify one of the network entities in the peer group as anomalous among the network entities in the peer group.
    Type: Application
    Filed: November 25, 2019
    Publication date: May 27, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Vikram Kumaran, Grégory Mermoud, Pierre-Andre Savalle
  • Merging and optimizing heterogeneous rulesets for device classification
    Patent number: 11232372
    Abstract: In one embodiment, a device classification service receives a plurality of device classification rulesets, each ruleset associating a set of device characteristics with a device type label. The device classification service forms a unified ruleset by resolving a conflict between conflicting device characteristics from two or more of the device classification rulesets. The device classification service trains a machine learning-based device classifier using the unified ruleset. The device classification service classifies, using telemetry data for a device in a network as input to the trained device classifier, the device with the device type label.
    Type: Grant
    Filed: November 9, 2018
    Date of Patent: January 25, 2022
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle
  • ADAPTIVE STRESS TESTING OF SD-WAN TUNNELS FOR WHAT-IF SCENARIO MODEL TRAINING
    Publication number: 20200382385
    Abstract: In one embodiment, a service in a network computes an expected information gain associated with rerouting traffic from a first tunnel onto a backup tunnel in the network. The service initiates, based on the expected information gain, rerouting of the traffic from the first tunnel onto the backup tunnel. The service obtains performance measurements for the traffic rerouted onto the backup tunnel. The service uses the performance measurements to train a machine learning model to predict whether rerouting traffic from the first tunnel onto the backup tunnel will satisfy a service level agreement (SLA) of the traffic.
    Type: Application
    Filed: May 29, 2019
    Publication date: December 3, 2020
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-Andre Savalle, Vinay Kumar Kolar
  • ANOMALY DETECTION OF MODEL PERFORMANCE IN AN MLOPS PLATFORM
    Publication number: 20210184958
    Abstract: In one embodiment, a service tracks performance of a machine learning model over time. The machine learning model is used to monitor one or more computer networks based on data collected from the one or more computer networks. The service also tracks performance metrics associated with training of the machine learning model. The service determines that a degradation of the performance of the machine learning model is anomalous, based on the tracked performance of the machine learning model and performance metrics associated with training of the model. The service initiates a corrective measure for the degradation of the performance, in response to determining that the degradation of the performance is anomalous.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-Andre Savalle
  • Detection and analysis of seasonal network patterns for anomaly detection
    Patent number: 10659333
    Abstract: In one embodiment, a device in a network determines cluster assignments that assign traffic data regarding traffic in the network to activity level clusters based on one or more measures of traffic activity in the traffic data. The device uses the cluster assignments to predict seasonal activity for a particular subset of the traffic in the network. The device determines an activity level for new traffic data regarding the particular subset of traffic in the network. The device detects a network anomaly by comparing the activity level for the new traffic data to the predicted seasonal activity.
    Type: Grant
    Filed: June 21, 2016
    Date of Patent: May 19, 2020
    Assignee: Cisco Technology, Inc.
    Inventors: Laurent Sartran, Pierre-André Savalle, Jean-Philippe Vasseur, Grégory Mermoud, Javier Cruz Mota, Sébastien Gay
  • HIERARCHICAL MODELS USING SELF ORGANIZING LEARNING TOPOLOGIES
    Publication number: 20200304530
    Abstract: In one embodiment, a device obtains characteristics of a first anomaly detection model executed by a first distributed learning agent in a network. The device receives a query from a second distributed learning agent in the network that requests identification of a similar anomaly detection to that of a second anomaly detection model executed by the second distributed learning agent. The device identifies, after receiving the query from the second distributed learning agent, the first anomaly detection model as being similar to that of the second anomaly detection model, based on the characteristics of the first anomaly detection model. The device causes the first anomaly detection model to be sent to the second distributed learning agent for execution.
    Type: Application
    Filed: June 5, 2020
    Publication date: September 24, 2020
    Inventors: Pierre-André Savalle, Grégory Mermoud, Laurent Sartran, Jean-Philippe Vasseur
  • Peer-to-peer feature exchange for edge inference of forecasting models
    Patent number: 11677819
    Abstract: In one embodiment, a network element in a network receives one or more machine learning models configured to make an inference about the network. The network element requests, according to a predefined peering plan, telemetry attribute data from one or more peer network elements specified by the peering plan. The network element receives the telemetry attribute data from the one or more peer network elements. The network element makes, using the one or more machine learning models, an inference about the network based in part on the received telemetry attribute data.
    Type: Grant
    Filed: March 26, 2020
    Date of Patent: June 13, 2023
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle, Vinay Kumar Kolar
  • EVENT-TRIGGERED MACHINE LEARNING FOR RARE EVENT FORECASTING IN A SOFTWARE DEFINED WIDE AREA NETWORK (SD-WAN)
    Publication number: 20210160148
    Abstract: In one embodiment, a service detects that an event of a particular event type has occurred in a software-defined wide area network (SD-WAN). The service activates, in response to detecting the occurrence of the event, a machine learning model to assess telemetry data regarding a first tunnel in the SD-WAN. The service predicts a failure of the first tunnel, based on the assessment of the telemetry data regarding the first tunnel by the machine learning model. The service proactively reroutes at least a subset of traffic on the first tunnel onto a second tunnel in the SD-WAN, in advance of the predicted failure of the first tunnel.
    Type: Application
    Filed: November 25, 2019
    Publication date: May 27, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-Andre Savalle
  • Predictive routing-based policy adjustments in software-defined networks
    Patent number: 11483234
    Abstract: In one embodiment, a device obtains routing forecasts for a software defined network. The device splits a particular routing policy for the software defined network into two or more routing policies, based on the routing forecasts. The device makes an evaluation as to whether the two or more routing policies should be reverted back into the particular routing policy. The device sends, to a user interface, data indicative of the particular routing policy that was split into the two or more routing policies and the evaluation as to whether the two or more routing policies should be reverted back into the particular routing policy.
    Type: Grant
    Filed: March 3, 2021
    Date of Patent: October 25, 2022
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle, Vinay Kumar Kolar
  • Estimating the efficacy of predictive routing for prospective deployments
    Patent number: 11632327
    Abstract: In one embodiment, a device obtains metadata for routing decisions made by a predictive routing service for a plurality of network deployments. The device identifies a network topology for a network deployment that does not use the predictive routing service. The device estimates, based on the metadata for routing decisions made by the predictive routing service, performance metrics for the predictive routing service were it to be used to make routing decisions for the network topology. The device sends, to a user interface, report data indicative of the performance metrics estimated for the predictive routing service were it to be used to make routing decisions for the network topology.
    Type: Grant
    Filed: May 27, 2021
    Date of Patent: April 18, 2023
    Assignee: Cisco Technology, Inc.
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle
  • Edge-based machine learning for encoding legitimate scanning
    Patent number: 10243980
    Abstract: In one embodiment, a device in a network receives an indication that a network anomaly detected by an anomaly detector of a first node in the network is associated with scanning activity in the network. The device receives labeled traffic data associated with the detected anomaly that identifies whether the traffic data is associated with legitimate or illegitimate scanning activity. The device trains a machine learning-based classifier using the labeled traffic data to distinguish between legitimate and illegitimate scanning activity in the network. The device deploys the trained classifier to the first node, to distinguish between legitimate and illegitimate scanning activity in the network.
    Type: Grant
    Filed: July 8, 2016
    Date of Patent: March 26, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle, Alexandre Honoré
Narrow Results

Filter by US Classification