Cyber security analysis of state estimators in electric power systems

By André M. H. Teixeira, Saurabh Amin, Henrik Sandberg, Karl Henrik Johansson, S. Sastry. IEEE Conference on Decision and Control, 2010

421 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/78747acbaee67e09857d29f29afbc4c6fbedfed9

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In Computer Networks and Communications

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Citations in the corpus

False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey (2017, background): “[23] propose a generalized approach to construct deception attacks on state estimation in smart grid, with specific target constraints.”
Attack Detection and Identification in Cyber-Physical Systems (2013, methodology): “tified as an issue of primary concern, see [19], [29] and [10],”
On Security Indices for State Estimators in Power Networks (2010, methodology): “Remark 2: An optimal solution to the above problem in terms of the 2-norm of the attack vector a has recently been presented in [7].”
Attacks against process control systems: risk assessment, detection, and response (2011, background): “Notable exceptions are the study of false data-injection attacks to state estimation in power grids [40–45], and electricity markets [46].”
Security analysis for Cyber-Physical Systems against stealthy deception attacks (2013, background): “This kind of attack has mainly been studied in the electric power distribution application [8] and some other applications can be found in [9], [10], [11].”
Detection in Adversarial Environments (2014, background): “INTRODUCTION EMBEDDED sensors, computation, and communication have enabled the development of sophisticated sensing devices [19] for a wide range of cyber physical applications that include safety monitoring, health-care, surveillance, traffic monitoring, and military applications [5], [6], [17], [2”
Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks (2012, background): “Since these assumptions are not justifiable in the context of adversarial attacks, there has been a recent increase in control systems security research [9]–[15].”
A systems and control perspective of CPS security (2019, methodology): “1) occur, references [37], [178]–[181] propose a solution based on robust signal processing techniques such as Least Trimmed Squares (LTS) to minimize the residue.”
Control-Theoretic Methods for Cyberphysical Security: Geometric Principles for Optimal Cross-Layer Resilient Control Systems (2015, background): “Du C !Y Other examples of monitors can be found in [13], [24], and [17] and in the section “Design of Attack Detection and Identification Monitors.”
Resilient Linear Classification: An Approach to Deal with Attacks on Training Data (2017, positive): “State estimation for an electric power system is analyzed in [47] assuming aackers know a partial model of the true system.”
On the Performance Analysis of Resilient Networked Control Systems Under Replay Attacks (2013, background): “Regarding attack detection, a p articular class of cyber attacks, namely false data injection, against state estimation is studied in [26], [29], [30].”