TWC: Small: Securing Smart Power Grids under Data Measurement Cyber Threats

TWC：小型：在数据测量网络威胁下保护智能电网

• 批准号: 1526166
• 负责人: Sara Eftekharnejad
• 金额: $ 49.96万
• 依托单位: Regents of the University of Idaho
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526166&HistoricalAwards=false
• 关键词: TWC; Small; Securing; Smart; Power

Power systems are changing with the rapid deployment of remote sensing devices such as Phasor Measurement Units (PMU) and integration of more capable Supervisory Control and Data Acquisition (SCADA) systems. PMU measurements, generated every second, are used by power system operators to make critical decisions. With more utilities adopting PMUs for real-time system monitoring, power systems are exposed to more cyber-threats targeting these devices.This research investigates means to determine the impacts of data intrusion on PMU devices, and will propose mitigation strategies. The outcomes will identify cyber-attacks that can result in cascading blackouts as well as the most critical components of power systems that are likely to be targeted by cyber threats. This multidisciplinary research will focus on three fundamental goals: (1) Quantifying the impact and severity of false data injection; (2) Detection of anomalies; and (3) Mitigation of the impacts. The project delineates differences between trivial and critical data manipulations and evinces the need to protect some measurements more than others. The project will systematically identify the most critical power system measurements that are best candidates for additional protection.The findings of this research will establish the foundations for protecting the most critical assets in power grids. As part of the broader impacts of this research, a diverse group of graduate and undergraduate students, especially women and underrepresented students can be trained in smart grid protection and planning. Mitigation methods proposed in this research can be extended to other complex networks and the proposed methods for identifying most critical components can be employed in other industries.

随着相量测量单元(PMU)等遥感设备的快速部署以及功能更强大的监控和数据采集(SCADA)系统的集成，电力系统正在发生变化。PMU测量值每秒产生一次，供电力系统操作员用来做出关键决策。随着越来越多的电力公司采用PMU进行实时系统监控，电力系统面临着更多针对这些设备的网络威胁。本研究探讨了确定数据入侵对PMU设备的影响的方法，并将提出缓解策略。结果将确定可能导致连锁停电的网络攻击，以及可能成为网络威胁目标的电力系统最关键的部件。这项多学科研究将集中在三个基本目标上：(1)量化虚假数据注入的影响和严重性；(2)异常检测；以及(3)减轻影响。该项目描述了琐碎数据操作和关键数据操作之间的差异，并表明需要比其他测量方法更好地保护某些测量结果。该项目将系统地确定最关键的电力系统测量，这些测量是额外保护的最佳候选者。这项研究的结果将为保护电网中最关键的资产奠定基础。作为这项研究更广泛影响的一部分，可以对不同的研究生和本科生群体，特别是女性和代表性不足的学生进行智能电网保护和规划方面的培训。本研究提出的缓解方法可以推广到其他复杂网络中，提出的识别最关键部件的方法也可以在其他行业中使用。