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Secure state estimation: Optimal guarantees against sensor attacks in the presence of noise

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TLDR
A secure state estimation algorithm is proposed and bounds are derived on the achievable state estimation error of this problem of estimating the state of a noisy linear dynamical system when a subset of sensors is arbitrarily corrupted by an adversary.
Abstract
Motivated by the need to secure cyber-physical systems against attacks, we consider the problem of estimating the state of a noisy linear dynamical system when a subset of sensors is arbitrarily corrupted by an adversary. We propose a secure state estimation algorithm and derive (optimal) bounds on the achievable state estimation error. In addition, as a result of independent interest, we give a coding theoretic interpretation for prior work on secure state estimation against sensor attacks in a noiseless dynamical system.

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Citations
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Journal ArticleDOI

Secure State Estimation for Cyber-Physical Systems Under Sensor Attacks: A Satisfiability Modulo Theory Approach

TL;DR: In this article, the authors present a secure state estimation algorithm that uses a satisfiability modulo theory approach to harness the complexity of the secure state estimator and provide guarantees on the soundness and completeness of the algorithm.
Posted Content

Secure State Estimation For Cyber Physical Systems Under Sensor Attacks: A Satisfiability Modulo Theory Approach

TL;DR: A novel algorithm is presented that uses a satisfiability modulo theory approach to harness the complexity of secure state estimation and leverages results from formal methods over real numbers to provide guarantees on the soundness and completeness of the algorithm.
Journal ArticleDOI

On Kalman Filtering with Compromised Sensors: Attack Stealthiness and Performance Bounds

TL;DR: A notion of attack stealthiness based on the Kullback–Leibler divergence measure is adopted and the worst case degradation induced by an attacker with a fixed stealthiness level is characterized, thereby proving tightness of the result.
Journal ArticleDOI

Secure State Estimation Against Sensor Attacks in the Presence of Noise

TL;DR: A secure state estimation algorithm is proposed, and bounds on the achievable state estimation error are derived given an upper bound on the number of attacked sensors.
Journal ArticleDOI

Secure State Estimation against Sensor Attacks in the Presence of Noise

TL;DR: In this paper, the problem of estimating the state of a noisy linear dynamical system when an unknown subset of sensors is arbitrarily corrupted by an adversary is considered, and a secure state estimation algorithm is proposed to derive (optimal) bounds on the achievable state estimation error given an upper bound on the number of attacked sensors.
References
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Journal ArticleDOI

Secure Estimation and Control for Cyber-Physical Systems Under Adversarial Attacks

TL;DR: A new simple characterization of the maximum number of attacks that can be detected and corrected as a function of the pair (A,C) of the system is given and it is shown that it is impossible to accurately reconstruct the state of a system if more than half the sensors are attacked.
Proceedings ArticleDOI

Secure control against replay attacks

TL;DR: This paper analyzes the effect of replay attacks on a control system and proposes a countermeasure that guarantees a desired probability of detection by trading off either detection delay or LQG performance, either by decreasing control accuracy or increasing control effort.
Book

Algebraic Codes for Data Transmission

TL;DR: This paper presents codes and algorithms for majority decoding based on the Fourier transform, as well as algorithms based on graphs, for linear block codes and beyond BCH codes.
Journal ArticleDOI

Control-Theoretic Methods for Cyberphysical Security: Geometric Principles for Optimal Cross-Layer Resilient Control Systems

TL;DR: The integration of cybertechnologies with physical processes increases system efficiencies and, at the same time, introduces vulnerabilities that undermine the reliability of critical infrastructures.
Journal ArticleDOI

Event-Triggered State Observers for Sparse Sensor Noise/Attacks

TL;DR: In this article, the authors describe two algorithms for state reconstruction from sensor measurements that are corrupted with sparse, but otherwise arbitrary, noise, motivated by the need to secure cyber-physical systems against a malicious adversary that can arbitrarily corrupt sensor measurements.
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