Identifying anomalies in user internet of things activity profile using analytic engine
US11126612B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 29, 2018 |
| Grant date | Sep 21, 2021 |
| Priority date | — |
| Expiry date | May 5, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are provided for identifying anomalies in an Internet of Things (IoT) activity profile of a user using an analytic engine. An exemplary method comprises obtaining data from a plurality of IoT devices of a user, wherein at least one IoT device comprises an agent device that performs an action on behalf of the user; applying the obtained data to a feature engineering module to convert the obtained data into time-series features that capture behavior and/or characteristics of an IoT environment of the user; and applying the time-series features to an analytic engine comprising a multi-variate anomaly detection method that learns one or more patterns in the IoT activity profile of the user for a normal state and identifies an anomaly with respect to an action performed by the agent device based on a health score indicating a deviation from the learned patterns.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.