NESG

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Data processing and networkmetrics

Members

Description

The networkmetrics research line seeks to take advantage of multivariate analysis and machine learning tools to tackle problems in communication networks, with cybersecurity as main example. An effective detection of cybersecurity incidents requires the combination of several and disparate data sources. This makes cybersec a typical Big Data problem, where the challenge is to handle tons of information from heterogeneous sources at a fastpace. In NESG, we develop new analysis methods to handle Multivariate Big Data, which are also of value in applications like IoT monitoring or Industry 4.0, and in other domains, like chemometrics, bioinformatics and personalized medicine.

  

Publications

  • Fuentes-García, N. M., González-Martínez, J. M., Maciá-Fernández, G. & Camacho, J (2019). PARAMO: enhanced data Pre-processing in Batch Multivariate Statistical Process Control. In 16th Scandinavian Sysmposium on Chemometrics (SSC16)), pages 10. [More] 
  • Fuentes-García, N. M., Camacho, J. & Maciá-Fernández, G (2019). Evaluación de mejoras en la monitorización estadística multivariante para la detección de anomalías en trafico ciclo-estacionario. In ́es Caro Lindo, A., ́ıa Villalba, L. J. & Orozco, A. L. (editors), V Jornadas Nacionales de Ciberseguridad, pages 277-278. [More] 
  • Fuentes-García, N. M., González-Martínez, J. M., Maciá-Fernández, G. & Camacho, J. (2019). PARAMO: enhanced data Pre-processing in Batch Multivariate Statistical Process Control. Journal of Chemometrics, . [More] 
  • Camacho, J., García-Giménez, J. M., Fuentes-García, N. M. & Maciá-Fernández, G. (2019). Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle. Preprint ArXiv, . [More] 
  • Camacho, J., Acar, E., Rasmussen, M. A. & Bro, R. (2019). Cross-product Penalized Component Analysis (XCAN). Preprint ArXiv, . [More]