Publications

@article{redondo-gutierrez_detecting_2022,

title = {Detecting malware using text documents extracted from spam email through machine learning},

author = {Luis Ángel Redondo-Gutierrez and Francisco Jáñez-Martino and Eduardo Fidalgo and Enrique Alegre and Víctor González-Castro and Rocío Alaiz-Rodríguez},

url = {https://dl.acm.org/doi/abs/10.1145/3558100.3563854},

year  = {2022},

date = {2022-01-01},

journal = {Proceedings of the 22nd ACM Symposium on Document Engineering},

pages = {1–4},

abstract = {This work introduces the "Spam Email Malware Detection - 600" (SEMD-600) dataset for detecting malware in spam emails using text analysis. It compares two text representation techniques (Bag of Words and TF-IDF) combined with three classifiers (SVM, Naive Bayes, and Logistic Regression). The combination of TF-IDF and Logistic Regression achieved the best performance, with a macro F1 score of 0.763.},

keywords = {Malware Detection, NLP, Spam Email, Text classification},

pubstate = {published},

tppubtype = {article}

}