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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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Journal ArticleDOI

Detection and reconstruction of measurements against false data injection and DoS attacks in distribution system state estimation: A deep learning approach

Y. Raghuvamsi, +1 more
- 01 Feb 2023 - 
TL;DR: In this article , an attention-based temporal convolutional denoising autoencoder is proposed which combines the advantages of the attention mechanism and temporal CNN to capture spatio-temporal information.
Posted Content

Optimal deception attack on networked vehicular cyber physical systems

TL;DR: In this article, a false data injection attack on a distributed cyber-physical system is considered, where a stochastic process with linear dynamics and Gaussian noise is measured by multiple agent nodes, each equipped with multiple sensors.
Book ChapterDOI

Impact Analysis of False Data Injection Attack on Smart Grid State Estimation Under Random Packet Losses

TL;DR: In this article, the impact of false data injection attack on smart grid state estimation under random packet losses is analyzed, and an attack vector range that can fool the attack detector is acquired.
Journal ArticleDOI

An Effective Attack-Resilient Kalman Filter-Based Approach for Dynamic State Estimation of Synchronous Machine

TL;DR: The basic KF-based method is enhanced by incorporating the dynamics of the attack vector into the system state-space model using an observer-based preprocessing stage and effectively handles the issues relevant to the modeling uncertainties and measurement noises/errors.
References
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False data injection attacks against state estimation in electric power grids

TL;DR: In this article, a new class of attacks, called false data injection attacks, against state estimation in electric power grids is presented and analyzed, under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations.
Journal ArticleDOI

Cyber–Physical System Security for the Electric Power Grid

TL;DR: The significance of cyber infrastructure security in conjunction with power application security to prevent, mitigate, and tolerate cyber attacks is highlighted and a layered approach is introduced to evaluating risk based on the security of both the physical power applications and the supporting cyber infrastructure.
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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