Resource Constrained Sensor Attacks by Minimizing Fisher Information

Ingvar Ziemann (1) , Henrik Sandberg (1)

1 KTH - KTH Royal Institute of Technology [Stockholm]

We analyze the impact of sensor attacks on a linear state estimation problem subject to variance and sparsity constraints. We show that the maximum impact in a leader-follower game where the attacker first chooses the distribution of an adversarial perturbation and the defender follows by choosing an estimator is characterized by a minimum Fisher information principle. In general, this is a nonlinear variational problem, but we show that it can be reduced to a finite-dimensional mixed integer SDP.

Domaines: Optimisation et contrôle [math.OC]

Ingvar Ziemann, Henrik Sandberg. Resource Constrained Sensor Attacks by Minimizing Fisher Information. 2020. ⟨hal-02977697⟩