Modeling Insider Threat Types in Cyber Organizations

被引:0
|
作者
Santos, Eunice E. [1 ]
Santos, Eugene, Jr. [2 ]
Korah, John [1 ]
Thompson, Jeremy E. [2 ]
Murugappan, Vairavan [1 ]
Subramanian, Suresh [1 ]
Zhao, Yan [2 ]
机构
[1] IIT, Dept Comp Sci, Chicago, IL 60616 USA
[2] Dartmouth Coll, Thayer Sch Engn, Hanover, NH 03755 USA
关键词
Bayesian knowledge bases (BKBs); insider threat; computational modeling; behavioral modeling; social modeling; trust; manipulation; cyber security;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Insider threats can cause immense damage to organizations of different types, including government, corporate, and non-profit organizations. Being an insider, however, does not necessarily equate to being a threat. Effectively identifying valid threats, and assessing the type of threat an insider presents, remain difficult challenges. In this work, we propose a novel breakdown of eight insider threat types, identified by using three insider traits: predictability, susceptibility, and awareness. In addition to presenting this framework for insider threat types, we implement a computational model to demonstrate the viability of our framework with synthetic scenarios devised after reviewing real world insider threat case studies. The results yield useful insights into how further investigation might proceed to reveal how best to gauge predictability, susceptibility, and awareness, and precisely how they relate to the eight insider types.
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页数:7
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