As computer networks have transformed in essential tools, their security has become a crucial problem for computer systems. Detecting unusual values fromlarge volumes of information produced by network traffic has acquired huge interest in the network security area. Anomaly detection is a starting point toprevent attacks, therefore it is important for all computer systems in a network have a system of detecting anomalous events in a time near their occurrence. Detecting these events can lead network administrators to identify system failures, take preventive actions and avoid a massive damage.This work presents, first, how identify network traffic anomalies through applying parallel computing techniques and Graphical Processing Units in two algorithms, one of them a supervised classification algorithm and the other based in traffic image processing.Finally, it is proposed as a challenge to resolve the anomalies detection using an unsupervised algorithm as Deep Learning.
CITATION STYLE
Barrionuevo, M., Lopresti, M., Miranda, N., & Piccoli, F. (2018). Secure Computer Network: Strategies and Challengers in Big Data Era. Journal of Computer Science and Technology, 18(03), e28. https://doi.org/10.24215/16666038.18.e28
Mendeley helps you to discover research relevant for your work.