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http://dx.doi.org/10.13089/JKIISC.2020.30.5.957

A Study on Development of Internal Information Leak Symptom Detection Model by Using Internal Information Leak Scenario & Data Analytics  

Park, Hyun-Chul (Samil PwC)
Park, Jin-Sang (KISA)
Kim, Jungduk (Chung-Ang University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.30, no.5, 2020 , pp. 957-966 More about this Journal
Abstract
According to the recent statistics of the National Industrial Security Center, about 80% of the confidential leak are caused by former and current employees in the case of domestic confidential leak accidents. Most of the information leak incidents by these insiders are due to poor security management system and information leak detection technology. Blocking confidential leak of insiders is a very important issue in the corporate security sector, but many previous researches have focused on responding to intrusions by external threats rather than by insider threats. Therefore, in this research, we design an internal information leak scenario to effectively and efficiently detect various abnormalities occurring in the enterprise, analyze the key indicators of the leak symptoms derived from the scenarios by using data analytics and propose a model that accurately detects leak activities.
Keywords
Internal information leak; scenario; data analytics; anomaly detection; risk indicators;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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