Paper2026
Material reviewed: AbstractThis paper presents DecoyTrace, a proactive cyber deception-based defense designed for strictly serverless decentralized federated learning (DFL) environments. According to the authors, the system deploys a mobile DecoyNode that generates decoy challenges using chaotic maps, disseminates a dual model (clean vs. decoy) based on neighbor trust, and evaluates behavior using three-state semantic metrics to identify and contain malicious sources. The authors report evaluations on the NEBULA platform across multiple configurations, datasets, and topologies.
NetworkApplicationDecoyAdversary engagement
Paper2026
Material reviewed: AbstractThis data article presents MURHCAD, a high-resolution honeynet dataset collected over 72 hours in June 2025 on Microsoft Azure, using three honeypots (Cowrie, Dionaea, and SentryPeer) deployed across four geographically dispersed virtual machines. According to the authors, the dataset comprises 132,425 attack events with enriched metadata (timestamps, IPs, geolocation, ports, and protocols) intended to support anomaly detection, protocol-misuse studies, and threat intelligence research.
CloudNetworkHoneypot
Paper2026
Material reviewed: AbstractThis report addresses the challenge of detecting AI-driven offensive cyber agents, proposing a strategic 'detection-in-depth' framework. According to the authors, five detection mechanisms are presented, including agent identifiers and agent honeypots, intended to support policymakers and industry against this emerging threat.
NetworkCloudHoneypotAdversary engagement
Paper2026
Material reviewed: AbstractThis paper presents DICOMHawk, a cyber-deception framework that emulates DICOM and PACS services with realistic interactions, dynamically populated medical records, and embedded honeytokens, designed to protect medical imaging infrastructure. According to the authors, in a 424-day deployment across multiple networks, DICOMHawk attracted more valid sessions than Dicompot, avoided honeypot detection, and captured 67 medical-related attacks from 15 unique IPs.
NetworkApplicationHoneypotHoneytoken
Open software2026
Material reviewed: Repository metadataDICOM Honeypot
NetworkHoneypot
Paper2026
Material reviewed: AbstractThis paper presents a behavior-driven attacker profiling framework built from empirical data collected in SSH honeypot deployments. The methodology parses complex command chains to identify behavioral patterns, organize them into hierarchical clusters, and map them to the MITRE ATT&CK framework for structured threat interpretation.
NetworkHoneypot
Paper2026
Material reviewed: AbstractThe authors propose an antifragile framework that uses cyber deception with adaptive decoys and dynamic network movements to generate adversarial signals, infer threat actor profiles and support proactive decisions. A cyber threat intelligence ontology and a knowledge graph with semantic attributes represent tactical and strategic relationships between attackers and targets.
NetworkDecoyAdversary engagement
Open software2026
Material reviewed: Repository metadataHoneypot type for Symfony forms
NetworkHoneypot
Paper2026
Material reviewed: AbstractThe paper describes an intrusion detection system that monitors live packets and uses predefined rules to detect suspicious activity rather than machine learning models. It includes a honeypot module with a fake login interface and human-readable explanations for detected anomalies.
NetworkHoneypot
Paper2026
Material reviewed: AbstractThe study investigates whether psychologically engineered "bias triggers" can exploit human attackers' Type I heuristic processing to degrade their performance. The authors use a high-fidelity cyber range where participants conduct network penetration with and without these triggers, analyzing operational telemetry.
NetworkDecoyAdversary engagement
Open software2026
Material reviewed: Repository metadataExpress honeypot for remote file inclusion (RFI) and local file inclusion (LFI).
NetworkHoneypot
Paper2026
Material reviewed: AbstractThis paper presents LDT-FRL, a defense framework combining temporal attention encoders, lightweight digital twins, and a federated reinforcement learning (PPO) agent capable of redirecting suspicious traffic to honeypots in IoMT (Internet of Medical Things) environments. According to the authors, the system was evaluated on public network traffic benchmarks, achieving high classification metrics and explainability via techniques such as SHAP and Grad-CAM.
IoTNetworkHoneypotAdversary engagement
Paper2026
Material reviewed: AbstractThe paper proposes a proactive defense approach using a high-interaction honeypot for DDoS detection and prevention. The honeypot captures IP addresses, malware and attacker tactics, feeding firewalls and traffic filters to block similar threats across the network.
NetworkHoneypot
Open software2026
Material reviewed: Repository metadataFortigate VPN-SSL Honeypot
NetworkHoneypot
Dataset or lab2026
Material reviewed: Public pageSSH interaction data collected by a honeypot between July and November 2025; event count comes from the authors.
NetworkHoneypot
Paper2026
Material reviewed: AbstractThe authors study attacker behavior across eleven SSH honeypots accepting both interactive and non-interactive sessions over fifteen days. According to the abstract, they found that the vast majority of authenticated sessions were non-interactive, challenging common assumptions in cyber deception research focused on interactive shells.
NetworkHoneypotDecoy
Open software2026
Material reviewed: Repository metadataGeneric Low Interaction Honeypot
NetworkHoneypot
Paper2026
Material reviewed: AbstractThis work, according to its authors, addresses DoS/DDoS mitigation by separating malicious from benign traffic using honeypots, framing the problem as a weighted MaxCut solved with variational quantum algorithms (QAOA). The authors describe a reproducible honeypot-to-QUBO pipeline, labeled temporal bipartite benchmark graphs, QAOA executions on IBM hardware, classical heuristic baselines, and a routing overhead analysis across quantum processor architectures.
NetworkHoneypot
Paper2026
Material reviewed: AbstractThe authors present HIVE-OT's design and implementation and evaluate the evidence supported by its process-coupled research core and historical exports, distinguishing the documented platform from a local implementation linking Modbus, a revised Rust water-treatment surrogate and SQLite. The study tests protocol behavior, command application and retained outcome representations, and audits two deployment exports containing 273978 and 842638 events.
OT/ICSNetworkHoneypot
Paper2026
Material reviewed: AbstractThis 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.
NetworkEndpointDecoy
Paper2026
Material reviewed: AbstractThe work presents HoneyPrompt, a multi-sensor fusion architecture for detecting and classifying autonomous AI agents that interact with industrial control systems. The authors deploy a maritime SCADA honeypot simulating a pipeline monitoring gateway across six protocols and instrument it with a graduated prompt injection acting as a sensor array.
OT/ICSNetworkHoneypotHoneytoken
Paper2026
Material reviewed: AbstractThis paper adapts the Honeyquest instrument to automatically evaluate LLM-based attacker judgment against cyber deception techniques. According to the authors, a cohort of 21 models from various providers was compared against a human baseline on reconnaissance tasks, finding that LLMs fall for traps at higher rates than humans and show a gap between recognizing deception in their reasoning and acting accordingly. The authors conclude that human-centered deception hypotheses do not reliably transfer to AI attackers.
NetworkHoneypotDecoy
Paper2026
Material reviewed: AbstractThis work presents Honeyval, an evaluation framework for LLM-powered HTTP honeypots. According to the authors, the framework uses AI hacking agents as attackers and diverse backend applications to reproducibly evaluate the performance and detectability of these honeypots compared to prior limited evaluation methods.
NetworkApplicationHoneypotDecoy
Open software2026
Material reviewed: Public pageThe statically read code defines configurable TCP bait ports that accept and close connections; it logs interactions and requests a firewall block for source IPs outside the allowlist.
NetworkHoneypotDecoy