  In recent years, SCADA (Supervisory Control and Data Acquisition) systems
have increasingly become the target of cyber attacks. SCADAs are no longer
isolated, as web-based applications expose strategic infrastructures to the
outside world connection. In a cyber-warfare context, we propose a Model
Predictive Control (MPC) architecture with adaptive resilience, capable of
guaranteeing control performance in normal operating conditions and driving
towards resilience against DoS (controller-actuator) attacks when needed. Since
the attackers' goal is typically to maximize the system damage, we assume they
solve an adversarial optimal control problem. An adaptive resilience factor is
then designed as a function of the intensity function of a Hawkes process, a
point process model estimating the occurrence of random events in time, trained
on a moving window to estimate the return time of the next attack. We
demonstrate the resulting MPC strategy's effectiveness in 2 attack scenarios on
a real system with actual data, the regulated Olginate dam of Lake Como.
