  Cyber-physical microgrids are vulnerable to stealth attacks that can degrade
their stability and operability by performing low-magnitude manipulations in a
coordinated manner. This paper formulates the interactions between CSAs and
microgrid defenders as a non-cooperative, zero-sum game. Additionally, it
presents a hybrid Moving Target Defense (MTD) strategy for distributed
microgrids that can dynamically alter local control gains to achieve resiliency
against Coordinated Stealth Attacks (CSAs). The proposed strategy reduces the
success probability of attack(s) by making system dynamics less predictable.
The framework also identifies and removes malicious injections by modifying
secondary control weights assigned to them. The manipulated signals are
reconstructed using an Artificial Neural Network (ANN)-based Digital Twin (DT)
to preserve stability. To guarantee additional immunity against instability
arising from gain alterations, MTD decisions are also validated (via utility
and best response computations) using the DT before actual implementation. The
DT is also used to find the minimum perturbation that defenders must achieve to
invalidate an attacker's knowledge effectively.
