Name
Title | ||
|---|---|---|
Sec-Buzzers: a Web Service for Exploring Cyber Security Emerging Topics based on Social Network Mining |
Abstract | ||
|---|---|---|
Recognition of information threats from social media can give advantages to incident response in very early stage. Previous related studies mostly focus on finding general hot terms instead of specific continuously-changing targets, such that usage of these methods may be limited when given specific theme as default. To our best knowledge so far, the proposed Sec-Buzzers is the first web-based service not only dedicated to finding the various emerging topics of cyber threats (i.e., nearly zero-day attacks) but also providing the possible remedy solutions. Unlike previous works, Sec-Buzzers mainly benefits from the strategy of community-oriented resource filtering and a novel modified topic association graph, such that a set of highly-contributing Twitter users was grouped, and information from that was explored then exploited. Demonstrations show that, by combining several measurements to quantify significance, Sec-Buzzers indeed uncovered emerging (or suddenly appearing) issues which are highly related to real cases about security threats. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2818869.2818897 | Proceedings of the ASE BigData & SocialInformatics 2015 |
Keywords | DocType | Citations |
information retrieval,information security,web service,cyber security,data mining | Conference | 0 |
PageRank | References | Authors |
0.34 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| chihhung hsieh | 1 | 0 | 0.34 |
| kuochen lee | 2 | 0 | 0.34 |
| chinghao mao | 3 | 0 | 0.34 |
| chiamin lai | 4 | 0 | 0.34 |
| Chiun-How Kao | 5 | 4 | 1.08 |
| jyunhan dai | 6 | 0 | 0.34 |