Robust Satisfaction of Metric Interval Temporal Logic Objectives in Adversarial Environments

Luyao Niu (), Bhaskar Ramasubramanian, Andrew Clark and Radha Poovendran
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Luyao Niu: Network Security Lab, Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA
Bhaskar Ramasubramanian: Electrical and Computer Engineering, Western Washington University, Bellingham, WA 98225, USA
Andrew Clark: Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
Radha Poovendran: Network Security Lab, Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA

Games, 2023, vol. 14, issue 2, 1-23

Abstract: This paper studies the synthesis of controllers for cyber-physical systems (CPSs) that are required to carry out complex time-sensitive tasks in the presence of an adversary. The time-sensitive task is specified as a formula in the metric interval temporal logic (MITL). CPSs that operate in adversarial environments have typically been abstracted as stochastic games (SGs); however, because traditional SG models do not incorporate a notion of time, they cannot be used in a setting where the objective is time-sensitive. To address this, we introduce durational stochastic games (DSGs). DSGs generalize SGs to incorporate a notion of time and model the adversary’s abilities to tamper with the control input (actuator attack) and manipulate the timing information that is perceived by the CPS (timing attack). We define notions of spatial, temporal, and spatio-temporal robustness to quantify the amounts by which system trajectories under the synthesized policy can be perturbed in space and time without affecting satisfaction of the MITL objective. In the case of an actuator attack, we design computational procedures to synthesize controllers that will satisfy the MITL task along with a guarantee of its robustness. In the presence of a timing attack, we relax the robustness constraint to develop a value iteration-based procedure to compute the CPS policy as a finite-state controller to maximize the probability of satisfying the MITL task. A numerical evaluation of our approach is presented on a signalized traffic network to illustrate our results.

Keywords: MITL specification; control synthesis; adversary; robustness; Stackelberg game (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2023
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