CyberdeceptionAtlas · Question → testES

Library / Paper

Paper

AEGIS-AI: Autonomous Threat Deception and Detection Using Honeypot Networks

The work proposes AEGIS-AI, a framework combining honeypots with reinforcement learning and deep neural networks to automate deception and detection of malicious activity. The authors describe real-time adaptive deception strategies via Markov Decision Processes and federated learning, and present formulas for evaluating deception effectiveness.

HoneypotAdversary engagementNetwork

What we know

The work proposes AEGIS-AI, a framework combining honeypots with reinforcement learning and deep neural networks to automate deception and detection of malicious activity. The authors describe real-time adaptive deception strategies via Markov Decision Processes and federated learning, and present formulas for evaluating deception effectiveness.

Evidence limits

Review limited to the Crossref-deposited abstract; the full text was not read and reported results were not independently verified.

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

Sources and provenance

  1. AEGIS-AI: Autonomous Threat Deception and Detection Using Honeypot Networks
    abstract · 2026-10-11

Reviewed: 2026-10-16. This record may change when new evidence is found.

RIS · BibTeX