针对低压配电系统的虚假数据注入攻击

Panagiotis I. Radoglou-Grammatikis, Christos Dalamagkas, T. Lagkas, Magda Zafeiropoulou, Maria Atanasova, Pencho Zlatev, Alexandros-Apostolos A. Boulogeorgos, V. Argyriou, E. Markakis, I. Moscholios, P. Sarigiannidis
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引用次数: 0

摘要

将传统电网转变为数字生态系统带来了显著的好处,例如能源消费者和公用事业公司之间的双向通信、自我监控和普遍控制。然而,鉴于遗留系统和通信协议的存在,智能电网的出现引发了严重的网络安全和隐私问题。本文主要研究针对低压配电系统的虚假数据注入(FDI)网络攻击,充分利用中间人(MITM)行为。第一次网络攻击的目标是智能电表和主动配电管理系统(ADMS)之间的通信,而第二次FDI网络攻击的目标是智能逆变器和ADMS之间的通信。在这两种情况下,网络攻击都会影响配电变压器的运行,从而造成毁灭性的后果。此外,本文还提供了一种基于人工智能(AI)的入侵检测系统(IDS),能够及时检测和缓解上述网络攻击。评价结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
False Data Injection Attacks against Low Voltage Distribution Systems
The transformation of the conventional electrical grid into a digital ecosystem brings significant benefits, such as two-way communication between energy consumers and utilities, self-monitoring and pervasive controls. However, the advent of the smart electrical grid raises severe cybersecurity and privacy concerns, given the presence of legacy systems and communications protocols. This paper focuses on False Data Injection (FDI) cyberattacks against a low-voltage distribution system, taking full advantage of Man In The Middle (MITM) actions. The first cyberattack targets the communication between a smart meter and an Active Distribution Management System (ADMS), while the second FDI cyberattack targets the communication between a smart inverter and ADMS. In both cases, the cyberattacks affect the operation of the distribution transformer, thus resulting in devastating consequences. Moreover, this paper provides an Artificial Intelligence (AI)-based Intrusion Detection System (IDS), detecting and mitigating the above cyberattacks in a timely manner. The evaluation results demonstrate the efficiency of the proposed IDS.
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