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HoneyContent: Wrapping Deception Storyline Content to Warrant Human and LLM Agent Attacker Evaluations of Deception Functions and Effects

This position paper suggests that presenting deception storyline content can influence how human attackers and Large Language Model (LLM) Agent attackers evaluate the authenticity of deception functions and effects on a network or host. The authors introduce HoneyContent, a practiced industry cyber deception model for designing and creating deception storyline content to 'wrap' or embed deception functions, integrating warranting theory and signaling theory, and visualize its use in an industry cyber deception scenario.

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What we know

This position paper suggests that presenting deception storyline content can influence how human attackers and Large Language Model (LLM) Agent attackers evaluate the authenticity of deception functions and effects on a network or host. The authors introduce HoneyContent, a practiced industry cyber deception model for designing and creating deception storyline content to 'wrap' or embed deception functions, integrating warranting theory and signaling theory, and visualize its use in an industry cyber deception scenario.

Evidence limits

Assessment based only on the Crossref deposited abstract; the full text was not reviewed and results, claims, or effectiveness of the approach were not independently verified.

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

Sources and provenance

  1. HoneyContent: Wrapping Deception Storyline Content to Warrant Human and LLM Agent Attacker Evaluations of Deception Functions and Effects
    abstract · 2026-10-11

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

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