False data injection attacks targeting power system generation control/scheduling and their mitigations

针对电力系统发电控制/调度的虚假数据注入攻击及其缓解措施

• 批准号: 566986-2021
• 负责人: Wang, XiaozheXZ
• 金额: $ 2.19万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753091
• 关键词: False; data; injection; attacks; targeting

Electric power systems are subject to cyberattacks. In this project, we intend to investigate false data injection attacks (FDIAs) targeting the automatic generation control (AGC) and the economic dispatch (ED) of electric power systems. Such a class of attacks may significantly affect the system frequency stability and result in huge economic loss and even catastrophic blackouts. Particularly, we will develop novel FDIA models targeting AGC and ED from the intruder's perspectives, evaluate the impacts of developed FDIAs on benchmark test systems, and then design effective mitigation methods against those FDIAs from the defender's viewpoint to reduce the negative impacts of the FDIAs and ensure the secure operation of power grids. The research outcomes will shed light on how we can better defend Canada's power grids and minimize catastrophic consequences on the security and integrity of the country's critical infrastructures against potential cyberattacks that are increasing both in frequency and severity.

电力系统受到网络攻击。在本项目中，我们打算研究针对电力系统的自动发电控制（AGC）和经济调度（艾德）的虚假数据注入攻击（FDIA）。这类攻击可能会严重影响系统的频率稳定性，造成巨大的经济损失，甚至造成灾难性的停电事故。特别是从入侵者的角度出发，针对AGC和艾德开发新的FDIA模型，评估已开发的FDIA对基准测试系统的影响，从防御者的角度出发，设计针对FDIA的有效缓解方法，以减少FDIA的负面影响，确保电网的安全运行。研究结果将阐明我们如何更好地保护加拿大的电网，并最大限度地减少对该国关键基础设施的安全性和完整性造成的灾难性后果，以应对频率和严重程度都在增加的潜在网络攻击。