Method and system for anomaly detection in a network
US12425420B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 24, 2023 |
| Grant date | Sep 23, 2025 |
| Priority date | — |
| Expiry date | Sep 19, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/20
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
For anomaly detection in a network, a temporal knowledge graph represents the network including interactions between network modules with a set of entities, a set of relations, and a set of timestamps. In a first step, temporal random walks are sampled from the temporal knowledge graph. These are transformed in a second step into temporal logical rules. After observing an event in the network—or in a different network—the observed event is classified in a third step regarding an anomaly, using the temporal logical rules. The temporal knowledge graph is used as a stream-based data structure to extract rules that identify typical temporal behavior of the network and is used to identify anomalies in a human-interpretable way. The anomaly detection task is framed as a quadruple classification problem, using the temporal logical rules and their respective groundings in the temporal knowledge graph to support the classification.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.