Related papers: Designing Sparse AC False Data Injection Attack
New methods that exploit sparse structures arising in smart grid networks are proposed for the state estimation problem when data injection attacks are present. First, construction strategies for unobservable sparse data injection attacks…
recent literature has proposed various detection and identification methods for FDIAs, but few studies have focused on a solution that would prevent such attacks from occurring. However, great strides have been made using deep learning to…
With the proliferation of smart devices and revolutions in communications, electrical distribution systems are gradually shifting from passive, manually-operated and inflexible ones, to a massively interconnected cyber-physical smart grid…
This paper considers the design of a distributed state-observer for discrete-time Linear Time-Invariant (LTI) systems in the presence of sensor attacks. We assume there is a network of observer nodes, communicating with each other over an…
In this paper a novel approach to co-design controller and attack detector for nonlinear cyber-physical systems affected by false data injection (FDI) attack is proposed. We augment the model predictive controller with an additional…
Cyberattack susceptibilities are introduced as the communication requirement increases with the incorporation of more renewable energy sources into DC microgrids. Parallel DC-DC converters are utilized to provide high current and supply the…
This paper addresses the problem of detecting false data injection (FDI) attacks in a distributed network without a fusion center, represented by a connected graph among multiple agent nodes. Each agent node is equipped with a sensor, and…
Consider the problem of mitigating the impact on data integrity of phasor measurement units (PMUs) given a GPS spoofing attack. We present a sparse error correction framework to treat PMU measurements that are potentially corrupted due to a…
Herein, design of false data injection attack on a distributed cyber-physical system is considered. A stochastic process with linear dynamics and Gaussian noise is measured by multiple agent nodes, each equipped with multiple sensors. The…
State estimation estimates the system condition in real-time and provides a base case for other energy management system (EMS) applications including real-time contingency analysis and security-constrained economic dispatch. Recent work in…
In this paper, we examine the factors that influence the success of false data injection (FDI) attacks in the context of both cyber and physical styles of reinforcement. Many works consider the FDI attack in the context of the ability to…
Fast and accurate detection of cyberattacks is a key element for a cyber-resilient power system. Recently, data-driven detectors and physics-based Moving Target Defences (MTD) have been proposed to detect false data injection (FDI) attacks…
We consider the problem of false data injection attacks modeled as additive disturbances in various parts of a general LTI feedback system and derive necessary and sufficient conditions for the existence of stealthy unbounded attacks. We…
Information theoretic sparse attacks that minimize simultaneously the information obtained by the operator and the probability of detection are studied in a Bayesian state estimation setting. The attack construction is formulated as an…
This paper is concerned with the problem of secure multi-sensors fusion estimation for cyber-physical systems, where sensor measurements may be tampered with by false data injection (FDI) attacks. In this work, it is considered that the…
This paper demonstrates that false data injection (FDI) attacks are extremely limited in their ability to cause physical consequences on $N-1$ reliable power systems operating with real-time contingency analysis (RTCA) and security…
Fault detection and identification (FDI) is critical for maintaining the safety and reliability of systems subject to actuator and sensor faults. In this paper, the problem of FDI for nonlinear control-affine systems under simultaneous…
Smart grids are inherently susceptible to various types of malicious cyberattacks that have all been documented in the recent literature. Traditional cybersecurity research on power systems often utilizes simplified models that fail to…
The use of low-precision analog-to-digital converters (ADCs) is a low-cost and power-efficient solution for a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system operating at sampling rates higher than a few Gsample/sec.…
Accurate state estimation is of paramount importance to maintain the power system operating in a secure and efficient state. The recently identified coordinated data injection attacks to meter measurements can bypass the current security…