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Journal ArticleDOI

A Review of False Data Injection Attacks Against Modern Power Systems

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TLDR
A comprehensive review of state-of-the-art in FDIAs against modern power systems is given and some potential future research directions in this field are discussed.
Abstract
With rapid advances in sensor, computer, and communication networks, modern power systems have become complicated cyber-physical systems. Assessing and enhancing cyber-physical system security is, therefore, of utmost importance for the future electricity grid. In a successful false data injection attack (FDIA), an attacker compromises measurements from grid sensors in such a way that undetected errors are introduced into estimates of state variables such as bus voltage angles and magnitudes. In evading detection by commonly employed residue-based bad data detection tests, FDIAs are capable of severely threatening power system security. Since the first published research on FDIAs in 2009, research into FDIA-based cyber-attacks has been extensive. This paper gives a comprehensive review of state-of-the-art in FDIAs against modern power systems. This paper first summarizes the theoretical basis of FDIAs, and then discusses both the physical and the economic impacts of a successful FDIA. This paper presents the basic defense strategies against FDIAs and discusses some potential future research directions in this field.

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Citations
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An Ethereum Blockchain-Based Prototype for Data Security of Regulated Electricity Market

TL;DR: This work proposes a decentralized Ethereum Blockchain-based end-to-end security prototype for a regulated electricity market such as the NZEM, which aims to enhance data security between the different layers of the current SCADA systems.
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On Addressing the Security and Stability Issues Due to False Data Injection Attacks in DC Microgrids—An Adaptive Observer Approach

TL;DR: In this paper , an observer-based methodology is proposed to detect and mitigate false data injection attacks in collaborative dc microgrids, where the ability of observers to effectively detect such attacks is complicated by the presence of unknown nonlinear constant power loads.
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Deep learning-based probabilistic anomaly detection for solar forecasting under cyberattacks

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Journal ArticleDOI

A modified model predictive control method for frequency regulation of microgrids under status feedback attacks and time-delay attacks

TL;DR: In this paper , a modified model predictive control (MPC) scheme is proposed for the secondary frequency control of MGs based on the online status switching method and generalized cross correlation (GCC) estimation to detect the real system status and time delay injected to the control system.
Book ChapterDOI

False data injection attacks on inverter-based microgrid in autonomous mode

TL;DR: This chapter studies the distributed load sharing problem of the microgrids operating in autonomous mode under FDI attacks, and introduces an FDI attack model, where the attacker can implant false data into the bus agents.
References
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Journal ArticleDOI

Cyber–Physical System Security for the Electric Power Grid

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Journal ArticleDOI

Malicious Data Attacks on the Smart Grid

TL;DR: Malicious attacks against power systems are investigated, in which an adversary controls a set of meters and is able to alter the measurements from those meters, and an optimal attack based on minimum energy leakage is proposed.
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