  Advanced persistent threat (APT) is a kind of stealthy, sophisticated, and
long-term cyberattack that has brought severe financial losses and critical
infrastructure damages. Existing works mainly focus on APT defense under stable
network topologies, while the problem under time-varying dynamic networks
(e.g., vehicular networks) remains unexplored, which motivates our work.
Besides, the spatiotemporal dynamics in defense resources, complex attackers'
lateral movement behaviors, and lack of timely defense make APT defense a
challenging issue under time-varying networks. In this paper, we propose a
novel game-theoretical APT defense approach to promote real-time and optimal
defense strategy-making under both periodic time-varying and general
time-varying environments. Specifically, we first model the interactions
between attackers and defenders in an APT process as a dynamic APT repair game,
and then formulate the APT damage minimization problem as the precise
prevention and control (PPAC) problem. To derive the optimal defense strategy
under both latency and defense resource constraints, we further devise an
online optimal control-based mechanism integrated with two backtracking-forward
algorithms to fastly derive the near-optimal solution of the PPAC problem in
real time. Extensive experiments are carried out, and the results demonstrate
that our proposed scheme can efficiently obtain optimal defense strategy in
54481 ms under seven attack-defense interactions with 9.64$\%$ resource
occupancy in stimulated periodic time-varying and general time-varying
networks. Besides, even under static networks, our proposed scheme still
outperforms existing representative APT defense approaches in terms of service
stability and defense resource utilization.
