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HUNT : USING HONEYTOKENS TO UNDERSTAND AND INFLUENCE THE EXECUTION OF AN ATTACK

The authors address the difficulty of distinguishing large-scale non-directional attacks from advanced persistent threats (APTs) and propose implementing honeytokens and honeypots as an intrusion detection system by deliberately placing traps within existing environments. They describe deploying a series of interconnected honeytokens, each with an exploitation difficulty level, to categorize attacks, profile the attacker and steer the execution flow into a maze-like scenario aimed at distracting, gathering forensic evidence and potentially identifying or deterring the attacker.

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What we know

The authors address the difficulty of distinguishing large-scale non-directional attacks from advanced persistent threats (APTs) and propose implementing honeytokens and honeypots as an intrusion detection system by deliberately placing traps within existing environments. They describe deploying a series of interconnected honeytokens, each with an exploitation difficulty level, to categorize attacks, profile the attacker and steer the execution flow into a maze-like scenario aimed at distracting, gathering forensic evidence and potentially identifying or deterring the attacker.

Evidence limits

Review based solely on the Crossref-deposited abstract; the full text was not read and results were not independently validated, and the abstract provides no details on actual implementation or effectiveness.

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

Sources and provenance

  1. HUNT : USING HONEYTOKENS TO UNDERSTAND AND INFLUENCE THE EXECUTION OF AN ATTACK
    abstract · 2026-10-11

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

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