A jointly optimal design of control and scheduling in networked systems under denial-of-service attacks

We consider the joint design of control and scheduling under stochastic Denial-of-Service (DoS) attacks in context networked systems. A sensor takes measurements system output forwards its dynamic state estimates to a remote controller over packet-dropping link. The determines optimal law for process using it receives. An attacker aims at degrading performance by increasing packet-dropout rate with DoS attack on sensor-controller channel. assume both are rational game-theoretic sense establish partially observable game derive control. Using programming we prove that policies can be designed separately without sacrificing optimality, making problem equivalent complete information game. employ Nash Q-learning solve solution is guaranteed constitute an ?-Nash equilibrium. Numerical examples provided illustrate interactions between attacker.