Name
Abstract | ||
|---|---|---|
As cybersecurity-related threats continue to increase, understanding how the field is changing over time can give insight into combating new threats and understanding historical events. We show how to apply dynamic topic models to a set of cybersecurity documents to understand how the concepts found in them are changing over time. We correlate two different data sets, the first relates to specific exploits and the second relates to cybersecurity research. We use Wikipedia concepts to provide a basis for performing concept phrase extraction and show how using concepts to provide context improves the quality of the topic model. We represent the results of the dynamic topic model as a knowledge graph that could be used for inference or information discovery. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/BigDataSecurity-HPSC-IDS49724.2020.00030 | 2020 IEEE 6th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS) |
Keywords | DocType | ISBN |
Cybersecurity,Knowledge Graph,Topic Modeling,Dynamic Topic Modeling | Conference | 978-1-7281-6874-6 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jennifer Sleeman | 1 | 49 | 7.99 |
| Timothy W. Finin | 2 | 7345 | 821.22 |
| Milton Halem | 3 | 86 | 29.78 |