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Generating high quality data for the protection of modern critical infrastructures

机译:为保护现代关键基础架构产生高质量数据

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This paper discusses the main issues regarding the procedures for generating High Quality Data (HQD) as support for conducting realistic cyber security studies on Modern Critical Infrastructures (CI). It identifies the most important requirements of what constitutes HQD: accuracy/realism, representation, and completeness. Based on these requirements, it discusses two strategies to achieve these requirements: the data collection strategy and the data generation strategy. While in the traditional Information & Technologies Communication (ICT) sector we find a variety of freely available datasets, in CI research data sources are scarce and of limited size. On the other hand, the data generation strategy has given birth to a new body of research built on the development of simulation software and of research testbeds. The paper describes two frameworks aimed at facilitating the generation of HQD for CI security research. Experimental results including the Tennessee-Eastman chemical process and the IEEE 14-bus electricity grid demonstrate the effectiveness of the developed frameworks.
机译:本文讨论了有关产生高质量数据(HQD)作为对现代关键基础设施(CI)进行现实网络安全研究的支持的主要问题。它确定了构成HQD的最重要要求:准确性/现实主义,表示和完整性。根据这些要求,它讨论了实现这些要求的两种策略:数据收集策略和数据生成策略。虽然在传统信息和技术通信(ICT)扇区中,我们发现各种可自由的数据集,但在CI研究中,稀缺和尺寸有限。另一方面,数据生成策略已经诞生了基于仿真软件和研究试验台的开发的新研究体。本文描述了两个框架,旨在促进CI安全研究的发电。实验结果包括田纳西州 - 伊斯特曼化学工艺和IEEE 14母电网展示了发达框架的有效性。

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