3 citations · 4 across the 11 of their papers we have counts for
12 papers
MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery
Haocheng Meng, Shaocheng Luo, Zhenyuan Liang +3
Unmanned Aerial Vehicles (UAVs) rely on measurements from Inertial Measurement Units (IMUs) to maintain stable flight. However, IMUs are susceptible to physical attacks, including…
Black-box Stealthy GPS Attacks on Unmanned Aerial Vehicles
Amir Khazraei, Haocheng Meng, Miroslav Pajic
This work focuses on analyzing the vulnerability of unmanned aerial vehicles (UAVs) to stealthy black-box false data injection attacks on GPS measurements. We assume that the quadc…
RadCloud: Real-Time High-Resolution Point Cloud Generation Using Low-Cost Radars for Aerial and Ground Vehicles
David Hunt, Shaocheng Luo, Amir Khazraei +4
In this work, we present RadCloud, a novel real time framework for directly obtaining higher-resolution lidar-like 2D point clouds from low-resolution radar frames on resource-cons…
From Spectral Theorem to Statistical Independence with Application to System Identification
Muhammad Abdullah Naeem, Amir Khazraei, Miroslav Pajic
High dimensional random dynamical systems are ubiquitous, including -- but not limited to -- cyber-physical systems, daily return on different stocks of S&P 1500 and velocity profi…
Vulnerability Analysis of Nonlinear Control Systems to Stealthy False Data Injection Attacks
Amir Khazraei, Miroslav Pajic
In this work, we focus on analyzing vulnerability of nonlinear dynamical control systems to stealthy false data injection attacks on sensors. We start by defining the stealthiness…
Stealthy Perception-based Attacks on Unmanned Aerial Vehicles
Amir Khazraei, Haocheng Meng, Miroslav Pajic
In this work, we study vulnerability of unmanned aerial vehicles (UAVs) to stealthy attacks on perception-based control. To guide our analysis, we consider two specific missions: (…
Attacks on Perception-Based Control Systems: Modeling and Fundamental Limits
Amir Khazraei, Henry Pfister, Miroslav Pajic
We study the performance of perception-based control systems in the presence of attacks, and provide methods for modeling and analysis of their resiliency to stealthy attacks on bo…
Resiliency of Nonlinear Control Systems to Stealthy Sensor Attacks
Amir Khazraei, Miroslav Pajic
In this work, we focus on analyzing vulnerability of nonlinear dynamical control systems to stealthy sensor attacks. We start by defining the notion of stealthy attacks in the most…
Optimal Myopic Attacks on Nonlinear Estimation
R. Spencer Hallyburton, Amir Khazraei, Miroslav Pajic
Recent high-profile incidents have exposed security risks in control systems. Particularly important and safety-critical modules for security analysis are estimation and control (E…
Learning-Based Vulnerability Analysis of Cyber-Physical Systems
Amir Khazraei, Spencer Hallyburton, Qitong Gao +2
This work focuses on the use of deep learning for vulnerability analysis of cyber-physical systems (CPS). Specifically, we consider a control architecture widely used in CPS (e.g.,…
Attack-Resilient State Estimation with Intermittent Data Authentication
Amir Khazraei, Miroslav Pajic
Network-based attacks on control systems may alter sensor data delivered to the controller, effectively causing degradation in control performance. As a result, having access to ac…
An Optimal Linear Dynamic Detection Method for Replay Attack in Cyber-Physical Systems
Amir Khazraei, Hamed Kebriaei, Farzad Rajaei Salmasi
The problem of detecting replay attack to the linear stochastic system with Kalman filer state estimator and LQG controller is addressed. To this end, a dynamic attack detector met…