Dynamic SNA-based anomaly detection using unsupervised learning
US7739211B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2006 |
| Grant date | Jun 15, 2010 |
| Priority date | — |
| Expiry date | Apr 15, 2029 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/145
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A method, system, and computer program product for enabling dynamic detection of anomalies occurring within an input graph representing a social network. More specifically, the invention provides an automated computer simulation technique that implements the combination of Social Network Analysis (SNA) and statistical pattern classification for detecting abnormal social patterns or events through the expanded use of SNA Metrics. The simulation technique further updates the result sets generated, based on observed occurrences, to dynamically determine what constitutes abnormal behavior, within the overall context of observed patterns of behavior.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.