Anomaly detection using circumstance-specific detectors
US10261851B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 7, 2015 |
| Grant date | Apr 16, 2019 |
| Priority date | — |
| Expiry date | Dec 5, 2035 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The technology disclosed relates to learning how to efficiently display anomalies in performance data to an operator. In particular, it relates to assembling performance data for a multiplicity of metrics across a multiplicity of resources on a network and training a classifier that implements at least one circumstance-specific detector used to monitor a time series of performance data or to detect patterns in the time series. The training includes producing a time series of anomaly event candidates including corresponding event information used as input to the detectors, generating feature vectors for the anomaly event candidates, selecting a subset of the candidates as anomalous instance data, and using the feature vectors for the anomalous instance data and implicit and/or explicit feedback from users exposed to a visualization of the monitored time series annotated with visual tags for at least some of the anomalous instances data to train the classifier.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.