Defensive technique
Simulated assets that can steer reconnaissance or make a suspicious interaction visible.
Research question
Definitions and technical considerations should be checked against the primary source. Atlas records are a selection tagged with this topic; a matching tag does not demonstrate operational outcomes.
Cross-reference
These counts describe tagged Atlas records, not the worldwide number of studies or offerings.
Linked library
The paper presents PHANTOM, a framework that generates honeytokens by encoding organisation-specific knowledge (domain names, service naming conventions, technology-stack idioms and realistic secret-value distributions) into a multi-component pipeline. The authors formalise a four-component believability score and use it to compare PHANTOM against a template-based baseline.
This paper presents a corpus of real scam- and spam-call conversations collected via an active voice-agent honeypot. According to the authors, the system adopts a plausible target persona to sustain interactions with fraudulent callers, recording audio, transcripts, and automatic labels. The study describes the collection system, record structure, and an evaluation of corpus realism and label quality, as well as benchmarking scam detectors trained on synthetic dialogue against real traffic.
The paper proposes a Deception Readiness Index (DRI) for ICS and OT cybersecurity programs. Using design science and qualitative analysis of public standards and guidance, it scores readiness across governance, architecture, monitoring, workforce, and operational safety domains, and applies the index to three synthetic critical-infrastructure profiles to identify gaps before deployment.
The authors propose TAB-DEN, a framework for IoT healthcare systems that combines a permissioned blockchain with Proof of Authority consensus for decentralized authentication, a hierarchical edge architecture of primary and secondary edge servers that compute trust scores in real time and redirect traffic according to trustworthiness, and deception-based edge nodes acting as honeypot-like environments to attract, isolate and profile attackers. The stated aim is to provide scalable and quantum-resistant security, recording intrusion events through a lattice-based post-quantum signature scheme so that attack records are immutable and verifiable on the distributed ledger.
The paper proposes a framework combining game theory with transformer-based components to quantify, model, and optimize cyber deception. The authors define deception attack-surface metrics and embed them in a signaling game, aiming to guide adaptive deception strategies.
The authors present a multi-attacker Bayesian Stackelberg framework for allocating honeypots in a directed network, modeling each attacker as a follower with a latent type and the defender as replanning via a DOBSS-style mixed-integer linear program under posterior beliefs. They aim to scale defense to realistic graphs using layered structures and pruning.