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<dc:title>Original and processed dataset of malware propagation in IoT networks with a SIR epidemiological model</dc:title>
<dc:creator>Sainz Villegas, Leticia</dc:creator>
<dc:creator>Casado Vara, Roberto Carlos</dc:creator>
<dc:creator>Basurto Hornillos, Nuño</dc:creator>
<dc:creator>Cambra Baseca, Carlos</dc:creator>
<dc:creator>Urda Muñoz, Daniel</dc:creator>
<dc:creator>Herrero Cosío, Álvaro</dc:creator>
<dc:subject>Mathematical epidemiology</dc:subject>
<dc:subject>Graph theory</dc:subject>
<dc:subject>Malware propagation</dc:subject>
<dc:subject>Data science</dc:subject>
<dc:subject>IoT network</dc:subject>
<dc:description>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.</dc:description>
<dc:date>2025-05-29T11:52:40Z</dc:date>
<dc:date>2025-05-29T11:52:40Z</dc:date>
<dc:date>2025-04-21</dc:date>
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<dc:identifier>10.71486/r4de-dj18</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>info:eu-repo/grantAgreement/INCIBE//AI4SECIoT/ES/Artificial Intelligence for Securing IoT Devices/</dc:relation>
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<dc:rights>Atribución 4.0 Internacional</dc:rights>
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<dc:coverage>start=2025-04; end=2025-04</dc:coverage>
<dc:publisher>Universidad de Burgos</dc:publisher>
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