Multivariate Analysis of Big Data in Software Defined Networks

Internet complexity is dramatically increasing and new innovative technologies are needed to handle rapidly growing volumes of diverse data from distributed sources. Software Defined Networking (SDN) has emerged as an interesting approach to handle massive tons of data efficiently, offering programmability in network functionalities. Big Data analysis techniques can be useful in the identification and troubleshooting of SDN problems, and the optimization of network performance. The MAD-SDN project proposes an approach based on multivariate big data analysis for network traffic classification and anomaly detection in the SDN environment.

Researcher: Katarzyna Wasielewska, PhD

Supervisor: José Camacho Páez, Full Professor

Period: two years, started on March 1, 2021

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 893146.