2026-04-21T12:08:18Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/105082025-05-30T00:05:11Zcom_10259_2604col_10259_5684
Sainz Villegas, Leticia
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Casado Vara, Roberto Carlos
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0000-0003-0198-696X
Basurto Hornillos, Nuño
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0000-0001-7289-4689
Cambra Baseca, Carlos
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0000-0001-5567-9194
Urda Muñoz, Daniel
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0000-0003-2662-798X
Herrero Cosío, Álvaro
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0000-0002-2444-5384
north=42.35; west=-3.706667; name=Burgos, Spain
start=2025-04; end=2025-04
2025-05-29T11:52:40Z
2025-05-29T11:52:40Z
2025-04-21
http://hdl.handle.net/10259/10508
10.71486/r4de-dj18
The dataset contains the data generated by an individual SIR model in an IoT network simulated by a graph for 20 time steps. This dataset is designed for training graph-based AI models for malware propagation detection in IoT networks.
This publication is part of the AI4SECIoT project ("Artificial Intelligence for Securing IoT Devices"), funded by the National Cybersecurity Institute (INCIBE), derived from a collaboration agreement signed between the National Institute of Cybersecurity (INCIBE) and the University of Burgos. This initiative is carried out within the framework of the Recovery, Transformation and Resilience Plan funds, financed by the European Union (Next Generation), the project of the Government of Spain that outlines the roadmap for the modernization of the Spanish economy, the recovery of economic growth and job creation, for solid, inclusive and resilient economic reconstruction after the COVID19 crisis, and to respond to the challenges of the next decade.
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eng
Universidad de Burgos
Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
Mathematical epidemiology
Graph theory
Malware propagation
Data science
IoT network
Informática
Inteligencia artificial
Computer science
Artificial intelligence
Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model
dataset
info:eu-repo/semantics/acceptedVersion
info:eu-repo/grantAgreement/INCIBE//AI4SECIoT/ES/Artificial Intelligence for Securing IoT Devices/
2025
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oai:riubu.ubu.es:10259/10508
2025-05-30 02:05:11.577
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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