Patents by Inventor Pierre A. Andre

Pierre A. Andre has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • DETECTING SPOOFING IN DEVICE CLASSIFICATION SYSTEMS
    Publication number: 20210329029
    Abstract: In various embodiments, a device classification service obtains device telemetry data indicative of declarative attributes of a device in a network and indicative of behavioral attributes of that device. The device classification service labels the device with a device type, based on the device telemetry data. The device classification service detects device type spoofing exhibited by the device using a model that models a relationship between the declarative attributes and the behavioral attributes. The device classification service initiates, based on the device type spoofing, a mitigation action regarding the device.
    Type: Application
    Filed: April 17, 2020
    Publication date: October 21, 2021
    Inventors: Jean-Philippe Vasseur, Pierre-André Savalle, Grégory Mermoud, David Tedaldi
  • REVISITING DEVICE CLASSIFICATION RULES UPON OBSERVATION OF NEW ENDPOINT ATTRIBUTES
    Publication number: 20210328986
    Abstract: In various embodiments, a device classification service uses an initial device classification rule to label each of a set of endpoint devices in a network as being of a particular device type. The device classification service identifies a particular attribute exhibited by at least a portion of the set of endpoint devices and was not previously used to generate the initial device classification rule. The device classification service generates one or more new device classification rules based in part on the particular attribute. The device classification service switches from using the initial device classification rule to label endpoint devices in the network to using the one or more new device classification rules to label endpoint devices in the network.
    Type: Application
    Filed: April 21, 2020
    Publication date: October 21, 2021
    Inventors: Jean-Philippe Vasseur, Pierre-André Savalle, Grégory Mermoud, David Tedaldi
  • Preserving privacy in exporting device classification rules from on-premise systems
    Patent number: 11153347
    Abstract: In one embodiment, a device in a network obtains data indicative of a device classification rule, a device type label associated with the rule, and a set of positive and negative feature vectors used to create the rule. The device replaces similar feature vectors in the set of positive and negative feature vectors with a single feature vector, to form a reduced set of feature vectors. The device applies differential privacy to the reduced set of feature vectors. The device sends a digest to a cloud service. The digest comprises the device classification rule, the device type label, and the reduced set of feature vectors to which differential privacy was applied. The service uses the digest to train a machine learning-based device classifier.
    Type: Grant
    Filed: May 29, 2019
    Date of Patent: October 19, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Pierre-Andre Savalle, Jean-Philippe Vasseur, Grégory Mermoud
  • Learning criticality of misclassifications used as input to classification to reduce the probability of critical misclassification
    Patent number: 11151476
    Abstract: In one embodiment, a device classification service that uses a machine learning-based device type classifier to classify endpoint devices with device types, identifies a set of device types having similar associated traffic telemetry features. The service obtains, via one or more user interfaces, feedback indicative of whether the device type classifier misclassifying an endpoint device having a particular device type in the set with another device type in the set would be a critical misclassification. The service trains, using the obtained feedback, a prediction model to predict an impact of misclassifying the particular device type as one of the other device types in the set of device types. The service also retrains the machine learning-based device type classifier based on a prediction from the prediction model.
    Type: Grant
    Filed: November 12, 2018
    Date of Patent: October 19, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle
  • Wheelchair caster assembly with anti-flutter feature
    Patent number: 11141331
    Abstract: A housing unit for a caster assembly comprising a hollow housing body forming an inner cavity. A first bearing is connected to the hollow housing body, the first bearing defining a rotational axis through its center, and configured to rotatably support a first portion of a stem supporting a caster for rotation about the rotational axis. A support assembly is connected to the hollow housing body, the support assembly being spaced from the first bearing, the support assembly having bearing segments concurrently defining a plain bearing around the rotational axis, the plain bearing configured to rotatably support a second portion of the stem during rotation about the rotational axis.
    Type: Grant
    Filed: January 26, 2018
    Date of Patent: October 12, 2021
    Assignee: MOTION COMPOSITES INC.
    Inventors: David Gingras, Pierre-Andre Couture, Michael Archambault Berube
  • Predicting network states for answering what-if scenario outcomes
    Patent number: 11146463
    Abstract: In one embodiment, a device constructs a set of controlled what-if input parameters for evaluating a what-if scenario in a network. The device uses the set of controlled what-if input parameters and state data indicative of a current state of the network as input to a network state model. The network state model predicts values for the state data conditioned on the what-if input parameters. The device predicts a key performance indicator (KPI) in the network by using the predicted values for the state data from the network state model as input to a machine learning-based KPI prediction model. The device initiates a routing change in the network based in part on the predicted KPI.
    Type: Grant
    Filed: June 5, 2019
    Date of Patent: October 12, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: David Tedaldi, Grégory Mermoud, Vinay Kumar Kolar, Jean-Philippe Vasseur, Pierre-Andre Savalle
  • Learning internal ranges from network traffic data to augment anomaly detection systems
    Patent number: 11140187
    Abstract: In one embodiment, a device in a network receives traffic records indicative of network traffic between different sets of host address pairs. The device identifies one or more address grouping constraints for the sets of host address pairs. The device determines address groups for the host addresses in the sets of host address pairs based on the one or more address grouping constraints. The device provides an indication of the address groups to an anomaly detector.
    Type: Grant
    Filed: July 22, 2019
    Date of Patent: October 5, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Laurent Sartran, Sébastien Gay, Pierre-André Savalle, Grégory Mermoud, Jean-Philippe Vasseur
  • PEER-TO-PEER FEATURE EXCHANGE FOR EDGE INFERENCE OF FORECASTING MODELS
    Publication number: 20210304026
    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: Application
    Filed: March 26, 2020
    Publication date: September 30, 2021
    Inventors: Grégory Mermoud, Jean-Philippe Vasseur, Pierre-André Savalle, Vinay Kumar Kolar
  • MODEL INTERPRETABILITY USING PROXY FEATURES
    Publication number: 20210304061
    Abstract: In one embodiment, a service identifies a set of attributes associated with a first machine learning model trained to make an inference about a computer network. The service obtains labels for each of the set of attributes, each label indicating whether its corresponding attribute is a probable cause of the inference. The service maps input features of the first machine learning model to those attributes in the set of attributes that were labeled as probable causes of the inference. The service generates a second machine learning model in part by using the mapped attributes to form a set of input features for the second machine learning model, whereby the input features of the first machine learning model and the input features of the second machine learning model differ.
    Type: Application
    Filed: March 27, 2020
    Publication date: September 30, 2021
    Inventors: Vinay Kumar Kolar, Jean-Philippe Vasseur, Pierre-André Savalle, Grégory Mermoud
  • UNSUPERVISED LEARNING OF LOCAL-AWARE ATTRIBUTE RELEVANCE FOR DEVICE CLASSIFICATION AND CLUSTERING
    Publication number: 20210303598
    Abstract: In various embodiments, a device classification service obtains data indicative of device attributes of a plurality of devices. The device classification service forms, based on the obtained data indicative of the device attributes, a concept graph that comprises nodes that represent different sets of the device attributes. The device classification service determines, by analyzing the concept graph, a relevance score for each of the device attributes that quantifies how relevant that attribute is to classifying a device by its device type. The device classification service uses the relevance scores for the device attributes to cluster the plurality of devices into device type clusters by their device attributes.
    Type: Application
    Filed: March 26, 2020
    Publication date: September 30, 2021
    Inventors: Grégory Mermoud, David Tedaldi, Pierre-André Savalle, Jean-Philippe Vasseur, Jürg Nicolaus Diemand
  • PROTECTING DEVICE CLASSIFICATION SYSTEMS FROM ADVERSARIAL ENDPOINTS
    Publication number: 20210297442
    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.
    Type: Application
    Filed: March 19, 2020
    Publication date: September 23, 2021
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Pierre-André Savalle, David Tedaldi
  • EXTRACTION OF PROTOTYPICAL TRAJECTORIES FOR AUTOMATIC CLASSIFICATION OF NETWORK KPI PREDICTIONS
    Publication number: 20210294818
    Abstract: In one embodiment, a service divides one or more time series for a network key performance (KPI) into a plurality of time series chunks. The service clusters the plurality of time series chunks into a plurality of clusters. The service identifies a sketch that represents a particular one of the clusters. The service associates a label with the identified sketch. The service applies the label to a new KPI time series by matching the sketch to the new KPI time series.
    Type: Application
    Filed: March 19, 2020
    Publication date: September 23, 2021
    Inventors: Pierre-André Savalle, Jean-Philippe Vasseur, Grégory Mermoud, Vinay Kumar Kolar
  • Refinement of device classification and clustering based on policy coloring
    Patent number: 11128534
    Abstract: In one embodiment, a device classification service receives data indicative of network traffic policies assigned to a plurality of device types. The device classification service associates measures of policy restrictiveness with the device types, based on the received data indicative of the network traffic policies assigned to the plurality of device types. The device classification service determines misclassification costs associated with a machine learning-based device type classifier of the service misclassifying an endpoint device of one of the plurality device types with another of the plurality of device types, based on their associated measures of policy restrictiveness. The device classification service adjusts the machine learning-based device type classifier to account for the determined misclassification costs.
    Type: Grant
    Filed: November 19, 2018
    Date of Patent: September 21, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Pierre-André Savalle, Jean-Philippe Vasseur
  • CASCADE-BASED CLASSIFICATION OF NETWORK DEVICES USING MULTI-SCALE BAGS OF NETWORK WORDS
    Publication number: 20210288876
    Abstract: In one embodiment, a device classification service uses feature vectors that represent how frequently one or more traffic features were observed in a network during different time windows to train a cascade of machine learning classifiers to label one or more devices in the network with a device type. The service receives traffic features of traffic associated with a particular device in the network, and then uses the cascade of machine learning classifiers to assign a device type label to the particular device based on the traffic features of the traffic associated with the particular device. The service initiates enforcement of a network policy regarding the device based on its device type based on the device type label assigned to the particular device.
    Type: Application
    Filed: May 21, 2021
    Publication date: September 16, 2021
    Inventors: Pierre-André Savalle, Jean-Philippe Vasseur, Grégory Mermoud
  • Virtual avatar animation based on facial feature movement
    Patent number: 11107261
    Abstract: The present disclosure generally relates to displaying visual effects such as virtual avatars. An electronic device having a camera and a display apparatus displays a virtual avatar that changes appearance in response to changes in a face in a field of view of the camera. In response to detecting changes in one or more physical features of the face in the field of view of the camera, the electronic device modifies one or more features of the virtual avatar.
    Type: Grant
    Filed: October 24, 2019
    Date of Patent: August 31, 2021
    Assignee: Apple Inc.
    Inventors: Nicolas Scapel, Guillaume Pierre André Barlier, Aurelio Guzman, Jason Rickwald
  • EMOJI RECORDING AND SENDING
    Publication number: 20210264656
    Abstract: The present disclosure generally relates to generating and modifying virtual avatars. An electronic device having a camera and a display apparatus displays a virtual avatar that changes appearance in response to changes in a face in a field of view of the camera. In response to detecting changes in one or more physical features of the face in the field of view of the camera, the electronic device modifies one or more features of the virtual avatar.
    Type: Application
    Filed: April 1, 2021
    Publication date: August 26, 2021
    Inventors: Guillaume Pierre André BARLIER, Sebastian BAUER, Aurelio GUZMAN, Nicolas SCAPEL, Giancarlo YERKES
  • Active learning for interactive labeling of new device types based on limited feedback
    Patent number: 11100364
    Abstract: In one embodiment, a device clusters traffic feature vectors for a plurality of endpoints in a network into a set of clusters. Each traffic feature vector comprises traffic telemetry data captured for one of the endpoints. The device selects one of the clusters for labeling, based in part on contextual data associated with the clusters that was not used to form the clusters. The device obtains a device type label for the selected cluster by providing data regarding the selected cluster and the contextual data associated with that cluster to a user interface. The device provides the device type label and the traffic feature vectors associated with the selected cluster for training a machine learning-based device type classifier.
    Type: Grant
    Filed: November 19, 2018
    Date of Patent: August 24, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Grégory Mermoud, Pierre-André Savalle, Jean-Philippe Vasseur, David Tedaldi
  • METHOD AND SYSTEM FOR IMPROVING QUALITY OF A DATASET
    Publication number: 20210240680
    Abstract: A method and system for improving quality of a dataset for which a labeling task is to be completed. A loop is repeated comprising: inferring, for each of the labeler identifiers in the dataset, an estimated proficiency value; inferring a predicted uncertainty value of correctness of the label for at least a subset of the raw data items; and receiving a trusted evaluation value of correctness for one or more labels of the subset of the raw data items for which the predicted uncertainty is inferred. The loop is repeated until the highest predicted uncertainty value in the dataset is below a threshold value.
    Type: Application
    Filed: January 31, 2020
    Publication date: August 5, 2021
    Inventors: Torsten SCHOLAK, Lee ZAMPARO, Hector PALACIOS, Kamil LEGAULT, Pierre-André NOËL, Krzysztof MAJEWSKI
  • FORECASTING NETWORK KPIs
    Publication number: 20210218641
    Abstract: In one embodiment, a service receives input data from networking entities in a network. The input data comprises synchronous time series data, asynchronous event data, and an entity graph that that indicates relationships between the networking entities in the network. The service clusters the networking entities by type in a plurality of networking entity clusters. The service selects, based on a combination of the received input data, machine learning model data features. The service trains, using the selected machine learning model data features, a machine learning model to forecast a key performance indicator (KPI) for a particular one of the networking entity clusters.
    Type: Application
    Filed: January 10, 2020
    Publication date: July 15, 2021
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Vinay Kumar Kolar, Pierre-Andre Savalle
  • Forecasting network KPIs
    Patent number: 11063842
    Abstract: In one embodiment, a service receives input data from networking entities in a network. The input data comprises synchronous time series data, asynchronous event data, and an entity graph that that indicates relationships between the networking entities in the network. The service clusters the networking entities by type in a plurality of networking entity clusters. The service selects, based on a combination of the received input data, machine learning model data features. The service trains, using the selected machine learning model data features, a machine learning model to forecast a key performance indicator (KPI) for a particular one of the networking entity clusters.
    Type: Grant
    Filed: January 10, 2020
    Date of Patent: July 13, 2021
    Assignee: Cisco Technology, Inc.
    Inventors: Jean-Philippe Vasseur, Grégory Mermoud, Vinay Kumar Kolar, Pierre-Andre Savalle