no code implementations • 16 Oct 2023 • Muhammad Abdullah Naeem, Amir Khazraei, Miroslav Pajic
In the light of these findings we set the stage for non-asymptotic error analysis in estimation of state transition matrix $A$ via least squares regression on observed trajectory by showing that element-wise error is essentially a variant of well-know Littlewood-Offord problem.
no code implementations • 6 Oct 2023 • Amir Khazraei, Miroslav Pajic
When the attacker has complete knowledge about the system, we show that if the closed loop system is incrementally exponentially stable while the open loop plant is incrementally unstable, then the system is vulnerable to stealthy yet impactful attacks on sensors.
no code implementations • 14 Jun 2022 • Amir Khazraei, Henry Pfister, Miroslav Pajic
Specifically, we consider a general setup with a nonlinear affine physical plant controlled with a perception-based controller that maps both the physical (e. g., IMUs) and perceptual (e. g., camera) sensing to the control input; the system is also equipped with a statistical or learning-based anomaly detector (AD).
no code implementations • 10 Mar 2021 • Amir Khazraei, Spencer Hallyburton, Qitong Gao, Yu Wang, Miroslav Pajic
This work focuses on the use of deep learning for vulnerability analysis of cyber-physical systems (CPS).