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首页> 外文会议>International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation >Using a Real-Time Cybersecurity Exercise Case Study to Understand Temporal Characteristics of Cyberattacks
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Using a Real-Time Cybersecurity Exercise Case Study to Understand Temporal Characteristics of Cyberattacks

机译：使用实时网络安全演习案例研究来了解网络攻击的时间特征

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摘要

Anticipatory cyber defense requires understanding of how cyber adversaries make decisions and adapt as cyberattacks unfold. This paper uses a dataset of qualitative observations conducted at a force on force ("paintball") exercise held at the 2015 North American International Cyber Summit (NAICS). By creating time series representations of the observed data, a broad range of data mining tools can be utilized to discover valuable verifiable knowledge about adversarial behavior. Two types of such analysis discussed in this work include clustering, which aims to find out what stages show similar temporal patterns, and peak detection for adaptation analysis. Collectively, this mixed methods approach contributes to understanding how adversaries progress through cyberattacks and adapt to any disruptions they encounter.
机译：预期的网络防御需要了解网络攻击者如何制定决策并随着网络攻击的发展而适应。本文使用在2015年北美国际网络峰会（NAICS）上进行的武力（“彩弹射击”）练习进行的定性观察数据集。通过创建观察数据的时间序列表示，可以使用各种数据挖掘工具来发现有关对抗行为的有价值的可验证知识。本工作中讨论的两种此类分析包括聚类（旨在发现哪些阶段显示出类似的时间模式）和峰检测以进行适应性分析。总而言之，这种混合方法有助于了解对手如何通过网络攻击发展并适应他们遇到的任何破坏。

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