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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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Proceedings ArticleDOI

Advanced Cyber-Physical Attack Classification with Extreme Gradient Boosting for Smart Transmission Grids

TL;DR: An ensemble learning-based attack classifier using extreme gradient boosting (XGBoost) that can effectively learn from the multi-sourced data to pinpoint attacks from normal and fault scenarios is proposed.
Journal ArticleDOI

Resilient Containment of Multigroup Systems Against Unknown Unbounded FDI Attacks

TL;DR: In this article , a fully distributed resilient control method for networked multigroup systems in the face of unknown unbounded false data injection (FDI) attacks is proposed to guarantee the uniformly ultimately bounded containment convergence.
Journal ArticleDOI

Cyber Attack Detection and Correction Mechanisms in a Distributed DC Microgrid

TL;DR: A virtual sensor-based framework is proposed for continuously monitoring and detecting malicious activities at the hardware level of a DCMG system by injecting false data at targeted nodes in an attempt to affect the voltage regulation and current sharing by modifying the onboard voltage and current sensors.
Journal ArticleDOI

A novel trust-based false data detection method for power systems under false data injection attacks

TL;DR: A trust model is first established to estimate the reliability of the system bus, then an algorithm is proposed to update the bus trust value, when all the trust value of neighbor buses at one bus node are quite low, then this bus is diagnosed as a malicious node and the false data are detected.
Journal ArticleDOI

Real-Time Locational Detection of Stealthy False Data Injection Attack in Smart Grid: Using Multivariate-Based Multi-Label Classification Approach

TL;DR: Extensive testing has shown that the proposed approach effectively improves the presence-detection accuracy for locating stealthy FDIAs in small and large systems under various attack conditions and provides a customized loss function for handling the class imbalance problem.
References
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False data injection attacks against state estimation in electric power grids

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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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