2026-07-20T10:20:46Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/105082025-05-30T00:05:11Zcom_10259_2604col_10259_5684

Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model Sainz Villegas, Leticia Casado Vara, Roberto Carlos Basurto Hornillos, Nuño Cambra Baseca, Carlos Urda Muñoz, Daniel Herrero Cosío, Álvaro Mathematical epidemiology Graph theory Malware propagation Data science IoT network 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. 2025-05-29T11:52:40Z 2025-05-29T11:52:40Z 2025-05-29T11:52:40Z 2025-04-21 dataset http://hdl.handle.net/10259/10508 10.71486/r4de-dj18 eng info:eu-repo/grantAgreement/INCIBE//AI4SECIoT/ES/Artificial Intelligence for Securing IoT Devices/ http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional north=42.35; west=-3.706667; name=Burgos, Spain start=2025-04; end=2025-04 Universidad de Burgos