Anomaly detection method, program, and system
US10133703B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 22, 2016 |
| Grant date | Nov 20, 2018 |
| Priority date | — |
| Expiry date | Sep 22, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2218/12
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method providing an analytical technique introducing label information into an anomaly detection model. Effective utilization of label information is based on introducing the degree of similarity between samples. Assuming, for example, there is a degree of similarity between normally labeled samples and no similarity between normally labeled and abnormally labeled samples. Also each sensor value is generated by the linear sum of a latent variable and a coefficient vector specific to each sensor. However, the magnitude of observation noise is formulated to vary according to the label information for the sensor values, and set so that normal label≤unlabeled≤anomalously labeled. A graph Laplacian is created based on the degree of similarity between samples, and determines the optimal linear transformation matrix according to a gradient method. A optimal linear transformation matrix is used to calculate an anomaly score for each sensor in the test samples.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.