One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method. Traditional COA attack search methods that passively search for attacks can be difficult, especially as the network gets bigger. To address these issues, new autonomous COA techniques are being developed, and among them, an intelligent spatial algorithm is designed in this paper for efficient operations in scalable networks. On top of the spatial search, a Monte-Carlo (MC)- based temporal approach is additionally considered for taking care of time-varying network behaviors. Therefore, we propose a spatio-temporal attack COA search algorithm for scalable and time-varying networks.

翻译：网络安全研究的关键课题之一是自主的COA(行动协作)攻击搜索方法。传统的COA攻击搜索方法可能很难被动地搜索攻击,特别是当网络规模扩大时。为了解决这些问题,正在开发新的自主COA技术,其中,本文件设计了一个智能空间算法,以便在可扩缩的网络中高效运行。除了空间搜索之外,基于蒙特-卡洛(Monte-Carlo)(MC)的时空方法还被进一步考虑来照顾时间变化的网络行为。因此,我们提议对可扩缩和时间变化的网络采用spatio-时间攻击COA搜索算法。