mlsanityData to 14 Oct 2026

Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain

arXiv 2211.03027 ↗First posted 6 Nov 2022cs.LG cs.CR cs.NIcited by 3

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Abstract (arXiv)

Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detection routes (SDR). This work extends previous efforts on developing RL methods for path analysis within enterprise networks. This work focuses on building SDR where the routes focus on exploring the network services while trying to evade risk. RL is utilized to support the development of these routes by building a reward mechanism that would help in realization of these paths. The RL algorithm is modified to have a novel warm-up phase which decides in the initial exploration which areas of the network are safe to explore based on the rewards and penalty scale factor.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 24 references that are in the map. First posted on arXiv 6 Nov 2022.

Builds on

10 of 24 references.

References · 10

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  3. 2015High-Dimensional Continuous Control Using Generalized Advantage Estimationcited by 2,026
  4. 2019Autonomous Penetration Testing using Reinforcement Learningcited by 33
  5. 2021Deep hierarchical reinforcement agents for automated penetration testingcited by 19
  6. 2021Using Cyber Terrain in Reinforcement Learning for Penetration Testingcited by 16
  7. 2021Crown Jewels Analysis using Reinforcement Learning with Attack Graphscited by 8
  8. 2022Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphscited by 8
  9. 2022A Layered Reference Model for Penetration Testing with Reinforcement Learning and Attack Graphscited by 4
  10. 2020Modeling Penetration Testing with Reinforcement Learning Using Capture-the-Flag Challenges: Trade-offs between Model-free Learning and A Priori Knowledgecited by 3

Built on by

Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2024Leveraging Reinforcement Learning in Red Teaming for Advanced Ransomware Attack Simulationscited by 1
  2. 2024Discovering Command and Control (C2) Channels on Tor and Public Networks Using Reinforcement Learningcited by 0
  3. 2025From Capabilities to Performance: Evaluating Key Functional Properties of LLM Architectures in Penetration Testingcited by 0