mlsanityData to 7 Oct 2026

Prospective Artificial Intelligence Approaches for Active Cyber Defence

arXiv 2104.09981 ↗First posted 20 Apr 2021cs.CR cs.LGcited by 11

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Abstract (arXiv)

Cybercriminals are rapidly developing new malicious tools that leverage artificial intelligence (AI) to enable new classes of adaptive and stealthy attacks. New defensive methods need to be developed to counter these threats. Some cybersecurity professionals are speculating AI will enable corresponding new classes of active cyber defence measures -- is this realistic, or currently mostly hype? The Alan Turing Institute, with expert guidance from the UK National Cyber Security Centre and Defence Science Technology Laboratory, published a research roadmap for AI for ACD last year. This position paper updates the roadmap for two of the most promising AI approaches -- reinforcement learning and causal inference - and describes why they could help tip the balance back towards defenders.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 8 of its 28 references that are in the map. First posted on arXiv 20 Apr 2021.

Builds on

8 of 28 references.

References · 8

  1. 2017Wild Patterns: Ten Years After the Rise of Adversarial Machine Learningcited by 411
  2. 2019Online Control with Adversarial Disturbancescited by 92
  3. 2019Deep Reinforcement Learning for Cyber Securitycited by 92
  4. 2020Finding Effective Security Strategies through Reinforcement Learning and Self-Playcited by 32
  5. 2016A Stochastic Model of Active Cyber Defense Dynamicscited by 2
  6. 2016Optimizing Active Cyber Defensecited by 2
  7. 2019The epidemiology of lateral movement: exposures and countermeasures with network contagion modelscited by 1
  8. 2019Features and Operation of an Autonomous Agent for Cyber Defensecited by 1

Built on by

Cited by year

Citing papers per year: 2021: 3; 2022: 3; 2023: 2; 2024: 1; 2025: 2.

11 papers.

  1. 2022Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulationcited by 37
  2. 2023Automated Cyber Defence: A Reviewcited by 19
  3. 2021Intrusion Prevention through Optimal Stoppingcited by 18
  4. 2023Learning Near-Optimal Intrusion Responses Against Dynamic Attackerscited by 13
  5. 2022Learning Security Strategies through Game Play and Optimal Stoppingcited by 5
  6. 2022A System for Interactive Examination of Learned Security Policiescited by 3
  7. 2021Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligencecited by 2
  8. 2021Autonomous Attack Mitigation for Industrial Control Systemscited by 1
  9. 2024Using Quantum Solved Deep Boltzmann Machines to Increase the Data Efficiency of RL Agentscited by 1
  10. 2025General Autonomous Cybersecurity Defense: Learning Robust Policies for Dynamic Topologies and Diverse Attackerscited by 1
  11. 2025Graphical Models for Decision-Making: Integrating Causality and Game Theorycited by 0