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http://dx.doi.org/10.15207/JKCS.2019.10.6.033

Topic Automatic Extraction Model based on Unstructured Security Intelligence Report  

Hur, YunA (Department of Computer Science and Egineering, Korea University)
Lee, Chanhee (Department of Computer Science and Egineering, Korea University)
Kim, Gyeongmin (Department of Computer Science and Egineering, Korea University)
Lim, HeuiSeok (Department of Computer Science and Egineering, Korea University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.6, 2019 , pp. 33-39 More about this Journal
Abstract
As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.
Keywords
Security; Intelligence Report; Analysis; Topic Modeling; Classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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