Detecting Unknown Insider Threat Scenarios

Q4 Computer Science
M. S. Lodhi, Rahul Kaul
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引用次数: 2

Abstract

Problems from the inside of an organization’s perimeters are a significant threat, since it is very difficult to differentiate them from outside activity. In this dissertation, evaluate an insider threat detection motto on its ability to detect different type of scenarios that have not previously been identify or contemplated by the developers of the system. We show the ability to detect a large variety of insider threat scenario instances We report results of an ensemble-based, unsupervised technique for detecting potential insider threat, insider threat scenarios that robustly achieves results. We explore factors that contribute to the success of the ensemble method, such as the number and variety of unsupervised detectors and the use of existing knowledge encoded in scenario based detectors made for different known activity patterns. We report results over the entire period of the ensemble approach and of ablation experiments that remove the scenario-based detectors.
检测未知的内部威胁场景
来自组织内部的问题是一个重大的威胁,因为很难将它们与外部活动区分开来。在本文中,评估一个内部威胁检测座右铭的能力,以检测不同类型的场景,这些场景以前没有被系统的开发人员识别或考虑。我们展示了检测各种内部威胁场景实例的能力。我们报告了一种基于集成的、无监督的技术的结果,用于检测潜在的内部威胁,内部威胁场景稳健地实现了结果。我们探索了有助于集成方法成功的因素,例如无监督检测器的数量和种类,以及为不同已知活动模式制作的基于场景的检测器中编码的现有知识的使用。我们报告了整个时期的集合方法和去除基于场景的探测器的烧蚀实验的结果。
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来源期刊
International Journal of Computer Science and Applications
International Journal of Computer Science and Applications Computer Science-Computer Science Applications
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期刊介绍: IJCSA is an international forum for scientists and engineers involved in computer science and its applications to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the IJCSA are selected through rigorous peer review to ensure originality, timeliness, relevance, and readability.
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