# Spatio-Temporal Attack Course-of-Action (COA) Search Learning for Scalable and Time-Varying Networks

arXiv: https://arxiv.org/abs/2209.00862 · HTML: https://mlsanity.com/paper/2209.00862/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 26 references that are in the map.
- First posted on arXiv 2 Sep 2022.

## Builds on (most cited first, 10 of 10)

- [Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications](https://mlsanity.com/paper/2008.02608/) (2020)
- [Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control](https://mlsanity.com/paper/2201.05843/) (2022)
- [Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networks](https://mlsanity.com/paper/2001.03611/) (2020)
- [Markov Decision Policies for Dynamic Video Delivery in Wireless Caching Networks](https://mlsanity.com/paper/1902.10932/) (2019)
- [Wireless Video Caching and Dynamic Streaming under Differentiated Quality Requirements](https://mlsanity.com/paper/1806.01594/) (2018)
- [Randomized Adversarial Imitation Learning for Autonomous Driving](https://mlsanity.com/paper/1905.05637/) (2019)
- [Dynamic Power Allocation and User Scheduling for Power-Efficient and Low-Latency Communications](https://mlsanity.com/paper/1807.00682/) (2018)
- [A Personalized Preference Learning Framework for Caching in Mobile Networks](https://mlsanity.com/paper/1904.06744/) (2019)
- [Joint Distributed Link Scheduling and Power Allocation for Content Delivery in Wireless Caching Networks](https://mlsanity.com/paper/1911.13010/) (2019)
- [Securing Heterogeneous IoT with Intelligent DDoS Attack Behavior Learning](https://mlsanity.com/paper/1711.06041/) (2017)

## Abstract (arXiv)

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.