mlsanityData to 7 Oct 2026

NSGZero: Efficiently Learning Non-Exploitable Policy in Large-Scale Network Security Games with Neural Monte Carlo Tree Search

arXiv 2201.07224 ↗First posted 17 Jan 2022cs.CR cs.AI cs.LGcited by 3

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Abstract (arXiv)

How resources are deployed to secure critical targets in networks can be modelled by Network Security Games (NSGs). While recent advances in deep learning (DL) provide a powerful approach to dealing with large-scale NSGs, DL methods such as NSG-NFSP suffer from the problem of data inefficiency. Furthermore, due to centralized control, they cannot scale to scenarios with a large number of resources. In this paper, we propose a novel DL-based method, NSGZero, to learn a non-exploitable policy in NSGs. NSGZero improves data efficiency by performing planning with neural Monte Carlo Tree Search (MCTS). Our main contributions are threefold. First, we design deep neural networks (DNNs) to perform neural MCTS in NSGs. Second, we enable neural MCTS with decentralized control, making NSGZero applicable to NSGs with many resources. Third, we provide an efficient learning paradigm, to achieve joint training of the DNNs in NSGZero. Compared to state-of-the-art algorithms, our method achieves significantly better data efficiency and scalability.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 10 of its 29 references that are in the map. First posted on arXiv 17 Jan 2022.

Builds on

10 of 29 references.

References · 10

  1. 2019Mastering Atari, Go, Chess and Shogi by Planning with a Learned Modelcited by 1,327
  2. 2020First return, then explorecited by 256
  3. 2017DeepStack: Expert-Level Artificial Intelligence in No-Limit Pokercited by 228
  4. 2016Deep Reinforcement Learning from Self-Play in Imperfect-Information Gamescited by 153
  5. 2016OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networkscited by 109
  6. 2015Deep Reinforcement Learning with a Natural Language Action Spacecited by 88
  7. 2021Learning and Planning in Complex Action Spacescited by 76
  8. 2018Deep Reinforcement Learning for Green Security Games with Real-Time Informationcited by 19
  9. 2021Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Playcited by 7
  10. 2021CFR-MIX: Solving Imperfect Information Extensive-Form Games with Combinatorial Action Spacecited by 4

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Cited by year

Citing papers per year: 2025: 3.

3 papers.

  1. 2025Equilibrium Policy Generalization: A Reinforcement Learning Framework for Cross-Graph Zero-Shot Generalization in Pursuit-Evasion Gamescited by 3
  2. 2025GraphChase: A Platform and Benchmark for Urban Network Security Gamescited by 2
  3. 2025R2PS: Worst-Case Robust Real-Time Pursuit Strategies under Partial Observabilitycited by 0