Multivariate clustering-based anomaly detection
US11037033B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2018 |
| Grant date | Jun 15, 2021 |
| Priority date | — |
| Expiry date | Mar 27, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2433
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A multivariate clustering-based anomaly detector can generate an event for consumption by an APM manager that indicates detection of an anomaly based on multivariate clustering analysis after topology-based feature selection. The anomaly detector accumulates time-series data across a series of time instants to form a multivariate time-series data slice or multivariate data slice. The anomaly detector then performs multivariate clustering analysis with the multivariate data slice. The anomaly detector determines whether a multivariate data slice is within a cluster of multivariate data slices. If the multivariate data slice is within the cluster and the cluster is a known anomaly cluster, then the anomaly detector generates an anomaly detection event indicating detection of the known anomaly. The anomaly detector can also determine that a multivariate data slice is within an unknown cluster and generate an event indicating detection of an unknown anomaly.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.