TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Indicator-based Behavior Ontology for Detecting Insider Threats in Network Systems |
| 영문제목(English Title) |
Indicator-based Behavior Ontology for Detecting Insider Threats in Network Systems |
| 저자(Author) |
Janghyuk Kauh
Wongi Lim
Koohyung Kwon
Jong-Eon Lee
Jung-Jae Kim
Minwoo Ryu
Si-Ho Cha
|
| 원문수록처(Citation) |
VOL 11 NO. 10 PP. 5062 ~ 5079 (2017. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
Malicious insider threats have increased recently, and methods of the threats are diversifying every day. These insider threats are becoming a significant problem in corporations and governments today. From a technology standpoint, detecting potential insider threats is difficult in early stage because it is unpredictable. In order to prevent insider threats in early stage, it is necessary to collect all of insiders’ data which flow in network systems, and then analyze whether the data are potential threat or not. However, analyzing all of data makes us spend too much time and cost. In addition, we need a large repository in order to collect and manage these data. To resolve this problem, we develop an indicator-based behavior ontology (IB2O) that allows us to understand and interpret insiders’ data packets, and then to detect potential threats in early stage in network systems including social networks and company networks. To show feasibility of the behavior ontology, we developed a prototype platform called Insider Threat Detecting Extractor (ITDE) for detecting potential insider threats in early stage based on the behavior ontology. Finally, we showed how the behavior ontology would help detect potential inside threats in network system. We expect that the behavior ontology will be able to contribute to detecting malicious insider threats in early stage. |
| 키워드(Keyword) |
Semantics
insider threat
behavior indicator
ontology
network system
security
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| 파일첨부 |
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