Provenance graph-oriented host intrusion detection method and system, and storage medium
US12182256B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 9, 2023 |
| Grant date | Dec 31, 2024 |
| Priority date | — |
| Expiry date | Aug 9, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F21/55
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention discloses a provenance graph-oriented host intrusion detection method and system, and a storage medium, which relates to the field of cyber security. The method includes: S1, acquiring provenance data of a host to be tested, to construct a provenance graph representing user behaviors; S2, mapping nodes in the provenance graph to roles, constructing a node feature matrix composed of feature vectors which can be used to represent attribute features, structural features, and inter-node interactive relationship of the nodes in the provenance graph, and mapping nodes having similar feature vectors to the same role; S3, performing an attention-guided attribute temporal random walk by comprehensively considering attributes of the nodes in the provenance graph, the temporal relationship between edges, and an attention parameter between different roles; and S4, converting the acquired attribute temporal random walk sequence into an embedding vector to extract a feature of the provenance graph, and performing intrusion anomaly detection. The present invention can perform deep representation learning on provenance data, reduce the workload of training a detection model, …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.