Abstract
Security of cyber-physical systems (CPS) is a challenge for increasingly integrated systems today. To analyze and design detection and defense mechanisms for CPSs requires new system frameworks. In this paper, we establish a zero-sum hybrid stochastic game model, that can be used for designing defense policies for cyber-physical systems against attackers of different types. The hybrid game model contains physical states described by the system dynamics, and a cyber state that represents the detection mode of the system. A system selects a subsystem by combining one controller, one estimator and one detector among a finite set of candidate components at each state. In order to provide scalable and real-time computation of the switching strategies, we propose a moving-horizon approach to solve the zero-sum hybrid stochastic game, and obtain a saddle-point equilibrium policy for balancing the system's security overhead and control cost. This approach leads to a real-time algorithm that yields a sequence of Nash equilibrium strategies which can be shown to converge. The paper illustrates these concepts using numerical examples, and we compare the results with previously known designs.
Original language | English (US) |
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Article number | 7039433 |
Pages (from-to) | 517-522 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
Volume | 2015-February |
Issue number | February |
DOIs | |
State | Published - 2014 |
Event | 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States Duration: Dec 15 2014 → Dec 17 2014 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization