Feature Analysis on the Containment Time for Cyber Security Incidents

Gulsum Akkuzu, Benjamin Azizl, Hanliu
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引用次数: 2

Abstract

Data mining techniques have been widely used as a common goal to discover hidden patterns from big data sets, so researchers have been motivated to make use of data in discovering useful information. The main contribution of this paper lies in its identifying relevant features from an open data set to predict the containment time of Cyber incidents. In particular, 13 relevant features were identified and selected to come up with a predictive model. Our results are discussed in the context of the organization‘s' information security.
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网络安全事件遏制时间特征分析
数据挖掘技术作为从大数据集中发现隐藏模式的共同目标已经被广泛使用,因此研究人员已经被激励利用数据来发现有用的信息。本文的主要贡献在于从开放数据集中识别相关特征,以预测网络事件的遏制时间。特别是,13个相关特征被识别和选择,以提出一个预测模型。我们的结果将在组织的“信息安全”上下文中进行讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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