Computer ScienceScientific Reports
Real-time botnet detection on large network bandwidths using machine learning
J. Velasco-mata, V. González-castro, et al.
This research presents an advanced machine learning approach for real-time botnet detection on large networks, achieving an impressive F1-score of 0.926. Conducted by Javier Velasco-Mata, Víctor González-Castro, Eduardo Fidalgo, and Enrique Alegre, this study demonstrates exceptional performance even in challenging network conditions. Discover the future of cybersecurity with this innovative solution!
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Medicine and Health
Detection of senescence using machine learning algorithms based on nuclear features
I. Duran, J. Pombo, et al.
Earth Sciences
A machine learning estimator trained on synthetic data for real-time earthquake ground-shaking predictions in Southern California
M. Monterrubio-velasco, S. Callaghan, et al.
Medicine and Health
A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects
A. Salomon, E. Gazit, et al.
Humanities
From remote sensing and machine learning to the history of the Silk Road: large scale material identification on wall paintings
S. Kogou, G. Shahtahmassebi, et al.
