CLAP: A Cross-Layer Analytic Platform for the Correlation of Cyber and Physical Security Events Affecting Water Critical Infrastructures

Gustavo Gonzalez-Granadillo, Rodrigo Díaz, Juan Caubet, Ignasi Garcia-Milà
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Abstract

Water CIs are exposed to a wide number of IT challenges that go from the cooperation and alignment between physical and cyber security teams to the proliferation of new vulnerabilities and complex cyber-attacks with potential disastrous consequences. Although novel and powerful solutions are proposed in the literature, most of them lack appropriate mechanisms to detect cyber and physical attacks in real time. We propose a Cross-Layer Analytic Platform (denoted as CLAP) developed for the correlation of Cyber and Physical security events affecting water CIs. CLAP aims to improve the detection of complex attack scenarios in real time based on the correlation of cyber and physical security events. The platform assigns appropriate severity values to each correlated alarm that will guide security analysts in the decision-making process of prioritizing mitigation actions. A series of passive and active attack scenarios against the target infrastructure are presented at the end of the paper to show the mechanisms used for the detection and correlation of cyber–physical security events. Results show promising benefits in the improvement of response accuracy, false rates reduction and real-time detection of complex attacks based on cross-correlation rules.
CLAP:影响水关键基础设施的网络和物理安全事件相关性的跨层分析平台
水ci面临着大量的IT挑战,从物理和网络安全团队之间的合作和协调,到新漏洞和复杂网络攻击的扩散,以及潜在的灾难性后果。虽然文献中提出了新颖而强大的解决方案,但大多数解决方案缺乏适当的机制来实时检测网络和物理攻击。我们提出了一个跨层分析平台(表示为CLAP),用于开发影响水ci的网络和物理安全事件的相关性。基于网络安全事件与物理安全事件的相关性,提高对复杂攻击场景的实时检测能力。该平台为每个相关警报分配适当的严重性值,这将指导安全分析师在确定缓解行动优先级的决策过程中。本文最后提出了针对目标基础设施的一系列被动和主动攻击场景,以展示用于检测和关联网络物理安全事件的机制。结果表明,基于相互关联规则的算法在提高响应精度、降低错误率和实时检测复杂攻击方面具有良好的效果。
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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