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In this paper, we study a security problem for attack detection in a class of cyber-physical systems consisting of discrete computerized components interacting with continuous agents. We consider an attacker that may inject recurring signals on both the physical dynamics of the agents and the discrete interactions. We model these attacks as additive unknown inputs with appropriate input signatures and timing characteristics. Using hybrid systems modeling tools, we design a novel hybrid attack monitor and, under reasonable assumptions, show that it is able to detect the considered class of recurrent attacks. Finally, we illustrate the general hybrid attack monitor using a specific finite time convergent observer and show its effectiveness on a simplified model of a cloud-connected network of autonomous vehicles.
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On the Estimation of Signal Attacks: A Dual Rate SD Control Framework
We consider the problem of estimating signal attacks injected into the actuators or sensors of control systems, assuming the attack is detectable, i.e., it can be seen at the output. We show that there exists a trade-off between attack rejection and control, and that the estimator design depends on the controller used. We use dual rate sampling to enhance detectability of the attacks and we provide different methods to design the estimator. The first method is by solving a model matching problem subject to causality constraints. The second method exploits dual rate sampling to accurately reconstruct the unknown input. The third method is using a dual rate unknown input observer.We provide conditions on the existence of these estimators, and show that dual rate unknown input observers always exist if the multirate system does not have a zero at 1.
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- Award ID(s):
- 1663460
- PAR ID:
- 10171187
- Date Published:
- Journal Name:
- European Control Conference
- Page Range / eLocation ID:
- 4380 to 4385
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.23919/ECC.2019.8796181
