| Title | Spatio-Temporal Attack Course-of-Action (COA) Search Learning for Scalable and Time-Varying Networks |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Lee, Haemin, Son, Seok Bin, Yun, Won Joon, Kim, Joongheon, Jung, Soyi, Kim, Dong Hwa |
| Conference Name | 2022 13th International Conference on Information and Communication Technology Convergence (ICTC) |
| Keywords | Behavioral sciences, convergence, information and communication technology, Monte Carlo methods, Network security, pubcrawl, Scalability, Scalable Security, Search methods |
| Abstract | 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. |
| DOI | 10.1109/ICTC55196.2022.9952999 |
| Citation Key | lee_spatio-temporal_2022 |
Spatio-Temporal Attack Course-of-Action (COA) Search Learning for Scalable and Time-Varying Networks