Ingeniería Telemática (Datos de investigación)
URI permanente para esta colecciónhttps://hdl.handle.net/11441/148219
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Conjunto de Datos Dataset of MITRE ATT&CK Enterprise network attack PCAPNG(2026-07-20) Muñoz Calle, Francisco Javier; Estepa Alonso, Antonio José; Estepa Alonso, Antonio José; Díaz Verdejo, Jesús; Ingeniería Telemática; Muñoz Calle, Francisco Javier; Muñoz Calle, Francisco Javier; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; TIC154: Departamento de Ingeniería TelemáticaThis repository contains a publicly available ATT&CK-oriented network attack dataset composed of manually generated and labeled PCAPNG captures associated with MITRE ATT&CK Enterprise techniques and sub-techniques observable from network traffic. The dataset was generated under controlled laboratory conditions using real offensive tools, vulnerable services, protocol-compliant implementations, and manually supervised attack execution procedures. The repository includes original PCAPNG captures, manually labeled flow annotations, attack metadata, Snort configurations and rule sets, and the pruning evaluation results employed throughout the experimental study. The objective of the dataset is to provide a realistic and reproducible benchmark for evaluating intrusion detection systems, ATT&CK-oriented monitoring approaches, traffic analysis methodologies, flow-based detection techniques, and rule pruning strategies.
Conjunto de Datos Labeled HTTP requests dataset: Dataset Biblio-US17(2023-07) Díaz Verdejo, Jesús; Estepa Alonso, Rafael María; Estepa Alonso, Antonio José; Muñoz Calle, Francisco Javier; Madinabeitia Luque, Germán; Ingeniería Telemática; Muñoz Calle, Francisco Javier; Estepa Alonso, Rafael María; Díaz Verdejo, Jesús; Muñoz Calle, Francisco Javier; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Ciencia e Innovación; Junta de Andalucía (Consejería de Transformación Económica, Industria, Conocimiento y Universidades); Universidad de Sevilla; TIC154: Departamento de Ingeniería TelemáticaThis dataset contains a set of anonymized and labeled HTTP requests (selected fields) from the logs of a real-in-production web server at the library of the University of Seville during 6.5 months in 2017. The dataset has been sanitized using a supervised methodology as proposed in: - Díaz-Verdejo, Jesús E.; Estepa, Antonio; Estepa, Rafael; Madinabeitia, German; Muñoz-Calle, Javier, "A methodology for conducting efficient sanitization of HTTP training datasets", Future Generation Computer Systems, vol. 109, pp. 67–82, 2020. https://doi.org/10.1016/j.future.2020.03.033.