Solving large-scale extensive-form network security games via neural fictitious self-play

• Main Authors: XUE, Wanqi, ZHANG, Youzhi, LI, Shuxin, WANG, Xinrun, AN, Bo, YEO, Chai Kiat
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2021
• 主題: Security and privacy; computational sustainability; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing; Theory and Algorithms
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/9140; https://ink.library.smu.edu.sg/context/sis_research/article/10143/viewcontent/Solving_LargeScale_pvoa.pdf
• 機構: Singapore Management University

Securing networked infrastructures is important in the real world. The problem of deploying security resources to protect against an attacker in networked domains can be modeled as Network Security Games (NSGs). Unfortunately, existing approaches, including the deep learning-based approaches, are in...