论文标题
使用智能电网中的重叠电测量测量检测异常
Detecting Anomalies using Overlapping Electrical Measurements in Smart Power Grids
论文作者
论文摘要
随着针对关键基础设施的网络攻击变得越来越频繁，能够快速识别和应对这些威胁变得越来越重要。这项工作调查了两个独立的系统，具有重叠的电测量结果，其目标是更快地识别异常。独立的系统包括Hist，Scada Historians和ION，自动仪阅读系统（AMR）。尽管先前的研究探讨了融合测量的好处，但尚未研究现有电气系统重叠测量的可能性。为此，我们探讨了结合重叠测量的潜在优势，以提高异常检测的速度/准确性并提供对收集的测量结果的其他验证。在本文中，我们表明合并重叠的测量结果为观察到的系统提供了更全面的图片。通过应用动态时间扭曲，发现更多异常 - 特别是在考虑两个重叠测量值的异常时，平均增加了349倍的异常。合并重叠的测量值时，与实验结果反映的数据相比，与非合并数据相比，可以实现高达785 \％的异常变化。
As cyber-attacks against critical infrastructure become more frequent, it is increasingly important to be able to rapidly identify and respond to these threats. This work investigates two independent systems with overlapping electrical measurements with the goal to more rapidly identify anomalies. The independent systems include HIST, a SCADA historian, and ION, an automatic meter reading system (AMR). While prior research has explored the benefits of fusing measurements, the possibility of overlapping measurements from an existing electrical system has not been investigated. To that end, we explore the potential benefits of combining overlapping measurements both to improve the speed/accuracy of anomaly detection and to provide additional validation of the collected measurements. In this paper, we show that merging overlapping measurements provide a more holistic picture of the observed systems. By applying Dynamic Time Warping more anomalies were found -- specifically, an average of 349 times more anomalies, when considering anomalies from both overlapping measurements. When merging the overlapping measurements, a percent change of anomalies of up to 785\% can be achieved compared to a non-merge of the data as reflected by experimental results.
