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Q-Cowrie: An adaptive honeypot to analyse attackers’ behaviour

The authors discuss applying reinforcement learning to improve response generation in honeypots and propose Q-Cowrie, a customization of the medium-interaction Cowrie honeypot intended to increase deception and support adaptive decisions while interacting with attackers. They report two experimental studies, one deploying Cowrie to capture attacks and model attacker decision-making with a Markov decision process, and another using Q-Cowrie to support adaptive interaction.

HoneypotAdversary engagementNetwork

What we know

The authors discuss applying reinforcement learning to improve response generation in honeypots and propose Q-Cowrie, a customization of the medium-interaction Cowrie honeypot intended to increase deception and support adaptive decisions while interacting with attackers. They report two experimental studies, one deploying Cowrie to capture attacks and model attacker decision-making with a Markov decision process, and another using Q-Cowrie to support adaptive interaction.

Evidence limits

This entry is based only on the title and abstract deposited in Crossref; it does not imply full-text reading, replication, working software, or independent validation of effectiveness.

Reviewed: author abstract. Full-text results were not analyzed.

Sources and provenance

  1. Q-Cowrie: An adaptive honeypot to analyse attackers’ behaviour
    abstract · 2026-10-11

Reviewed: 2026-10-13. This record may change when new evidence is found.

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