5 citations · 21 across the 11 of their papers we have counts for
11 papers
A Verifiable Framework for Cyber-Physical Attacks and Countermeasures in a Resilient Electric Power Grid
Zhigang Chu, Andrea Pinceti, Ramin Kaviani +10
In this paper, we investigate the feasibility and physical consequences of cyber attacks against energy management systems (EMS). Within this framework, we have designed a complete…
Reliability Makes It Difficult for False Data Injection Attacks to Cause Physical Consequences
Zhigang Chu, Jiazi Zhang, Oliver Kosut +1
This paper demonstrates that false data injection (FDI) attacks are extremely limited in their ability to cause physical consequences on reliable power systems operating with…
Detecting Load Redistribution Attacks via Support Vector Models
Zhigang Chu, Oliver Kosut, Lalitha Sankar
A machine learning-based detection framework is proposed to detect a class of cyber-attacks that redistribute loads by modifying measurements. The detection framework consists of a…
A Nonlinear Regression Method for Composite Protection Modeling of Induction Motor Loads
Soumya Kundu, Zhigang Chu, Yuan Liu +6
Protection equipment is used to prevent damage to induction motor loads by isolating them from power systems in the event of severe faults. Modeling the response of induction motor…
Can Predictive Filters Detect Gradually Ramping False Data Injection Attacks Against PMUs?
Zhigang Chu, Andrea Pinceti, Reetam Sen Biswas +3
Intelligently designed false data injection (FDI) attacks have been shown to be able to bypass the -test based bad data detector (BDD), resulting in physical consequences (suc…
Vulnerability Assessment of N-1 Reliable Power Systems to False Data Injection Attacks
Zhigang Chu, Jiazi Zhang, Oliver Kosut +1
This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. Prior work has shown that an attacker-d…
Unobservable False Data Injection Attacks against PMUs: Feasible Conditions and Multiplicative Attacks
Zhigang Chu, Jiazi Zhang, Oliver Kosut +1
This paper studies false data injection (FDI) attacks against phasor measurement units (PMUs). As compared to the conventional bad data detector (BDD), an enhanced BDD utilizing th…
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition
Jiazi Zhang, Zhigang Chu, Lalitha Sankar +1
This paper studies the vulnerability of phasor measurement units (PMUs) to false data injection (FDI) attacks. Prior work demonstrated that unobservable FDI attacks that can bypass…
Vulnerability Assessment of Large-scale Power Systems to False Data Injection Attacks
Zhigang Chu, Jiazi Zhang, Oliver Kosut +1
This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. Prior work has shown that an attacker-d…
Can Attackers with Limited Information Exploit Historical Data to Mount Successful False Data Injection Attacks on Power Systems?
Jiazi Zhang, Zhigang Chu, Lalitha Sankar +1
This paper studies physical consequences of unobservable false data injection (FDI) attacks designed only with information inside a sub-network of the power system. The goal of thi…
Evaluating Power System Vulnerability to False Data Injection Attacks via Scalable Optimization
Zhigang Chu, Jiazi Zhang, Oliver Kosut +1
Physical consequences to power systems of false data injection cyber-attacks are considered. Prior work has shown that the worst-case consequences of such an attack can be determin…