Patent · US Active

Utilizing machine learning models to process resource usage data and to determine anomalous usage of resources

US11836578B2 · kind B2 · utility

0Cited by

2References

20Claims

0Family size

Assignee

ACCENTURE GLOBAL SOLUTIONS LIMITED · IE

Inventors

Kun Qiu · San Diego, US
Vijay Desai · San Diego, US
Laser Seymour Kaplan · San Diego, US
Durga Kalyan Ganjapu · North York, CA
Daniel Marcus Lombardo · San Diego, US

Key dates

Filing date	Aug 26, 2019
Grant date	Dec 5, 2023
Priority date	—
Expiry date	Aug 20, 2040

Classification

Technology area (CPC G)Physics
CPC primaryG06F11/3433
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A device receives historical data associated with multiple cloud computing environments, trains one or more machine learning models, with the historical data, to generate trained machine learning models that generate outputs, and trains a model with the outputs to generate a trained model. The device receives particular data, associated with a cloud computing environment, that includes data identifying usage of resources associated with the cloud computing environment, and processes the particular data, with the trained machine learning models, to generate anomaly scores indicating anomalous usage of the resources associated with the cloud computing environment. The device processes the one or more anomaly scores, with the trained model, to generate a final anomaly score indicating anomalous usage of at least one of the resources associated with the cloud computing environment, and performs one or more actions based on the final anomaly score.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.