Publications

@article{castano_automating_2024,

title = {Automating cybersecurity TTP classification based on nnstructured attack descriptions},

author = {Felipe Castaño and Amaia Gil-Lerchundi and Raúl Orduna-Urrutia and Eduardo Fidalgo and Rocío Alaiz-Rodríguez},

url = {https://idus.us.es/items/1566b428-106f-4ace-8d17-0835566c60bf},

year  = {2024},

date = {2024-01-01},

journal = {Jornadas Nacionales de Investigación en Ciberseguridad (JNIC)(9ª. 2024. Sevilla)(2024), pp. 46-50.},

abstract = {This paper introduces WAVE-27K, a large dataset of unstructured CTI descriptions covering 27 MITRE techniques and 7 tactics. It contains 22,539 single-technique samples and 5,262 multi-technique samples, making it the largest dataset in its category. A BERT-based model trained on WAVE-27K achieved a 97% micro F1-score, demonstrating its quality for machine learning applications in cybersecurity.},

note = {Publisher: Universidad de Sevilla. Escuela Técnica Superior de Ingeniería Informática},

keywords = {BERT, CTI, cyber threat intelligence, machile learning, SOC operations},

pubstate = {published},

tppubtype = {article}

}