Patents by Inventor Jeffrey W. HASKELL

Jeffrey W. HASKELL 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).

  • ONLINE ANOMALY DETECTION OF VECTOR EMBEDDINGS
    Publication number: 20240064165
    Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an anomaly detection system. Some aspects of this disclosure include a method for detecting anomaly in a network device. The method includes determining one or more similarity values between a flow vector corresponding to a flow associated with the network device and one or more flow clusters associated with the network device. The method further includes determining a maximum similarity value as a maximum of the one or more similarity values and comparing the maximum similarity value to a threshold. The method also includes, in response to the maximum similarity value being equal to or greater than the threshold, updating a flow cluster associated with the maximum similarity value. The method also includes, in response to the maximum similarity measure being less than the threshold, detecting the anomaly in the network device.
    Type: Application
    Filed: October 18, 2023
    Publication date: February 22, 2024
    Applicant: Extreme Networks, Inc.
    Inventors: Giacomo BERNARDI, Donagh HORGAN, Jeffrey W. HASKELL, Markus NISPEL
  • Online anomaly detection of vector embeddings
    Patent number: 11824876
    Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an anomaly detection system. Some aspects of this disclosure include a method for detecting anomaly in a network device. The method includes determining one or more similarity values between a flow vector corresponding to a flow associated with the network device and one or more flow clusters associated with the network device. The method further includes determining a maximum similarity value as a maximum of the one or more similarity values and comparing the maximum similarity value to a threshold. The method also includes, in response to the maximum similarity value being equal to or greater than the threshold, updating a flow cluster associated with the maximum similarity value. The method also includes, in response to the maximum similarity measure being less than the threshold, detecting the anomaly in the network device.
    Type: Grant
    Filed: January 31, 2020
    Date of Patent: November 21, 2023
    Assignee: Extreme Networks, Inc.
    Inventors: Giacomo Bernardi, Donagh Horgan, Jeffrey W. Haskell, Markus Nispel
  • Online Anomaly Detection of Vector Embeddings
    Publication number: 20210243210
    Abstract: Disclosed herein are system, method, and computer program product embodiments for providing an anomaly detection system. Some aspects of this disclosure include a method for detecting anomaly in a network device. The method includes determining one or more similarity values between a flow vector corresponding to a flow associated with the network device and one or more flow clusters associated with the network device. The method further includes determining a maximum similarity value as a maximum of the one or more similarity values and comparing the maximum similarity value to a threshold. The method also includes, in response to the maximum similarity value being equal to or greater than the threshold, updating a flow cluster associated with the maximum similarity value. The method also includes, in response to the maximum similarity measure being less than the threshold, detecting the anomaly in the network device.
    Type: Application
    Filed: January 31, 2020
    Publication date: August 5, 2021
    Applicant: Extreme Networks, Inc.
    Inventors: Giacomo BERNARDI, Donagh HORGAN, Jeffrey W. HASKELL, Markus NISPEL