Name
Title | ||
|---|---|---|
Representing network knowledge using provenance-aware formalisms for cyber-situational awareness. |
Abstract | ||
|---|---|---|
Due to the volume, variety, and veracity of network data available, information fusion and reasoning techniques are needed to support network analysts’ cyber-situational awareness. These techniques rely on formal knowledge representation to define the network semantics with data provenance at various levels of granularity. To this end, this paper proposes the Communication Network Topology and Forwarding Ontology, a state-of-the-art ontology that enables the formal, unified representation of complex network concepts regardless of the type of the data source. The implementation of this ontology allows network analysts to represent expert knowledge and query network data fused from disparate data sources. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.procs.2018.07.206 | Procedia Computer Science |
Keywords | Field | DocType |
Knowledge representation,ontology engineering,cybersecurity | Ontology,Knowledge representation and reasoning,Telecommunications network,Information retrieval,Situation awareness,Computer science,Disparate system,Complex network,Artificial intelligence,Rotation formalisms in three dimensions,Machine learning,Semantics | Conference |
Volume | ISSN | Citations |
126 | 1877-0509 | 1 |
PageRank | References | Authors |
0.36 | 7 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leslie F. Sikos | 1 | 17 | 3.73 |
| Markus Stumptner | 2 | 1253 | 185.56 |
| Wolfgang Mayer | 3 | 61 | 9.07 |
| Catherine Howard | 4 | 17 | 5.77 |
| Shaun Voigt | 5 | 2 | 1.39 |
| Dean Philp | 6 | 2 | 1.39 |