Abnormal behavior detection of enterprise entities using time-series data
US11310247B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 21, 2016 |
| Grant date | Apr 19, 2022 |
| Priority date | — |
| Expiry date | Mar 14, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine-readable medium may store instructions executable by a processing resource to access log data of an enterprise and extract time-series data of an enterprise entity from the log data. The time-series data may include measured feature values of a set of selected features over a series of time periods. The instructions may be further executable to train a predictive model specific to the enterprise entity using the time-series data, wherein the predictive model is to generate, for a particular time period, a predicted feature value for each of the selected features; access actual feature values of the enterprise entity for the particular time period; apply first-level deviation criteria to the actual feature value and the predicted feature value of each selected feature to identify deviant features of the enterprise entity; and apply second-level deviation criteria to the identified deviant features to identify the enterprise entity as behaving abnormally.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.