过程系统中增强的安全性——评估知识援助

A. Lohfink, V. M. Memmesheimer, Frederike Gartzky, C. Garth
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引用次数: 0

摘要

我们展示了对Lohfink等人开发的过程安全系统[14]的改进的评估结果,以支持运营技术网络中的分类分析。为了确保对设备读数中的异常做出快速和适当的反应,该系统将异常检测结果和设备读数进行通信,以结合人类的专业知识和经验。它将螺旋图与异常检测结果相结合,利用数据的周期性行为。为了支持决策、增加信任和支持系统中的合作,我们将其增强为知识辅助。中心知识库允许在分析期间在用户和支持人员之间共享知识。它由描述事件的本体和包含示例传感器读数集合的数据库组成,其中包含注释和可视化参数。相关知识被自动提出,并直接合并到可视化中,以提供与应用程序紧密耦合的帮助,而没有额外的障碍。这种集成旨在为可视化设备读数中正确和快速检测异常提供额外支持。我们通过详细的用户研究,从有效性、效率、用户满意度和认知负荷等方面评估了我们对过程安全系统的改进。对比原来的系统和增强后的系统,我们可以得出结论,我们的设计是如何缩小专业分析师和外行之间的知识差距的。此外,我们提出并讨论了结果和对我们未来研究的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Enhanced Security in Process System - Evaluating Knowledge Assistance
We present evaluation results of our enhancements to the Security in Process System [14] developed by Lohfink et al. to support triage analysis in operational technology networks. To ensure fast and appropriate reactions to anomalies in device readings, this system communicates anomaly detection results and device readings to incorporate human expertise and experience. It exploits periodical behavior in the data combining spiral plots with results from anomaly detection. To support decisions, increase trust, and support cooperation in the system we enhanced it to be knowledge-assisted. A central knowledge base allows sharing knowledge between users and support during analysis. It consists of an ontology describing incidents, and a data base holding collections of exemplary sensor readings with annotations and visualization parameters. Related knowledge is proposed automatically and incorporated directly in the visualization to provide assistance that is closely coupled to the application, without additional hurdles. This integration is designed aiming on additional support for correct and fast detection of anomalies in the visualized device readings. We evaluate our enhancements to the Security in Process System in terms of effectiveness, efficiency, user satisfaction, and cognitive load with a detailed user study. Comparing the original and enhanced system, we are able to draw conclusions as to how our design narrows the knowledge gap between professional analysts and laymen. Furthermore, we present and discuss the results and impact on our future research.
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