Published July 10, 2025 | Version v1

Multi-Regional Cloud Honeynet Dataset: A Distributed T-Pot Honeypot Deployment Across Azure Regions for Cyber Threat Analysis

  • 1. ROR icon Universidad Rey Juan Carlos

Contributors

Hosting institution:

Description

This dataset includes a high-resolution honeynet dataset that can be used for independent analysis of the patterns of cyberattacks around the world. The information, which was gathered over 72 hours (June 9–11, 2025) on Microsoft Azure, includes 132,425 distinct attack events that were recorded by three honeypots (Cowrie, Dionaea, and Sentrypeer) spread across four geographically separated virtual machines. In addition to derived temporal features (hour, day, weekday, date), each event record contains enriched metadata such as UTC timestamps, source/destination IPs, autonomous system and organizational mappings, geolocation coordinates, targeted ports, and honeypot identifiers. Standardized protocol classifications are also included.

Files

CloudHoneyNetDataset.zip

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Additional details

Related works

Is supplemented by
10.5281/zenodo.15716264 (DOI)

Funding

European Union
CONVENIO DE COLABORACIÓN ENTRE LA UNIVERSIDAD REY JUAN CARLOS Y LA S.M.E INSTITUTO NACIONAL DE CIBERSEGURIDAD DE ESPAÑA M.P., S.A. PARA LA PROMOCIÓN DE PROYECTOS ESTRATÉGICOS DE CIBERSEGURIDAD EN ESPAÑA PLAN DE RECUPERACIÓN, TRANSFORMACIÓN Y RESILIENCIA- FINANCIADO POR LA UNIÓN EUROPEA - NEXT GENERATION EU F1086 / ETD202300129ETD
Agencia Estatal de Investigación
LATENTIA PID2022-140786NB-C32/AEI/10.13039/501100011033

Dates

Submitted
2025-07-10

Software

Repository URL
https://doi.org/10.5281/zenodo.15716734
Programming language
Python