Patents by Inventor David Benjamin Krisiloff

David Benjamin Krisiloff 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).

  • Churn-aware machine learning for cybersecurity threat detection
    Patent number: 11954571
    Abstract: Churn-aware training of a classifier which reduces the difference between predictions of two different models, such as a prior generation of a classification model and a subsequent generation. A second dataset of labelled data is scored on a prior generation of a classification model, wherein the prior generation was trained on a first dataset of labelled data. A subsequent generation of a classification model is trained with the second dataset of labelled data, wherein in training of the subsequent generation, weighting of at least some of the labelled data in the second dataset, such as labelled data threat yielded an incorrect classification, is adjusted based on the score of such labelled data in the prior generation.
    Type: Grant
    Filed: January 25, 2023
    Date of Patent: April 9, 2024
    Assignee: GOOGLE LLC
    Inventors: David Benjamin Krisiloff, Scott Coull
  • Churn-aware machine learning for cybersecurity threat detection
    Patent number: 11568316
    Abstract: Churn-aware training of a classifier which reduces the difference between predictions of two different models, such as a prior generation of a classification model and a subsequent generation. A second dataset of labelled data is scored on a prior generation of a classification model, wherein the prior generation was trained on a first dataset of labelled data. A subsequent generation of a classification model is trained with the second dataset of labelled data, wherein in training of the subsequent generation, weighting of at least some of the labelled data in the second dataset, such as labelled data threat yielded an incorrect classification, is adjusted based on the score of such labelled data in the prior generation.
    Type: Grant
    Filed: April 7, 2020
    Date of Patent: January 31, 2023
    Assignee: Mandiant, Inc.
    Inventors: David Benjamin Krisiloff, Scott Coull
  • CHURN-AWARE MACHINE LEARNING FOR CYBERSECURITY THREAT DETECTION
    Publication number: 20210314333
    Abstract: Churn-aware training of a classifier which reduces the difference between predictions of two different models, such as a prior generation of a classification model and a subsequent generation. A second dataset of labelled data is scored on a prior generation of a classification model, wherein the prior generation was trained on a first dataset of labelled data. A subsequent generation of a classification model is trained with the second dataset of labelled data, wherein in training of the subsequent generation, weighting of at least some of the labelled data in the second dataset, such as labelled data threat yielded an incorrect classification, is adjusted based on the score of such labelled data in the prior generation.
    Type: Application
    Filed: April 7, 2020
    Publication date: October 7, 2021
    Inventors: David Benjamin Krisiloff, Scott Coull