2 papers
cs.CR2025
Anomaly detection in network flows using unsupervised online machine learning
Alberto Miguel-Diez, Adrián Campazas-Vega, Ãngel Manuel Guerrero-Higueras +2
Nowadays, the volume of network traffic continues to grow, along with the frequency and sophistication of attacks. This scenario highlights the need for solutions capable of contin…
cs.CR2025
A systematic literature review of unsupervised learning algorithms for anomalous traffic detection based on flows
Alberto Miguel-Diez, Adrián Campazas-Vega, Claudia Ãlvarez-Aparicio +2
The constant increase of devices connected to the Internet, and therefore of cyber-attacks, makes it necessary to analyze network traffic in order to recognize malicious activity.…