  We present a resource-planning game for the cybersecurity of network control
systems (NCS). The NCS is assumed to be operating in closed-loop using a linear
state-feedback $\mathcal{H}_2$ controller. A zero-sum, two-player Stackelberg
game (SG) is developed between an attacker and a defender for this NCS. The
attacker aims to disable communication of selected nodes and thereby render the
feedback gain matrix to be sparse, leading to degradation of closed-loop
performance. The defender, on the other hand, aims to prevent this loss by
investing in the protection of targeted nodes. Both players trade their
$\mathcal{H}_2$-performance objectives for the costs of their actions. The
standard backward induction method is modified to determine a cost-based
Stackelberg equilibrium (CBSE) that provides the optimal performance payoffs to
both players while saving their individual costs. We analyze the dependency of
a CBSE on the relative budgets of the players as well as on the "important"
network nodes, which must be preserved to achieve a reliable
$\mathcal{H}_2$-performance. Additionally, we consider NCS models with
uncertainties and develop robust, long-term security investment games based on
this cost-based SG. The proposed games are validated using an example of
wide-area control of electric power systems, where it is demonstrated that
reliable and robust defense is feasible unless the defender is much more
resource-limited than the attacker.
