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Archivio Istituzionale della Ricerca
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EnglishThanks to the rapid advances in Internet-based applications, data acquisition and storage technologies, petabyte-sized network data collections are becoming more and more common, thus prompting the need for scalable data analysis solutions. By leveraging today’s ubiquitous many-core computer architectures and the increasingly popular cloud computing paradigm, the applicability of data mining algorithms to these large volumes of network data can be scaled up to gain interesting insights. This paper proposes NEMICO, a comprehensive Big Data mining system targeted to network traffic flow analyses (e.g., traffic flow characterization, anomaly detection, multiplelevel pattern mining). NEMICO comprises new approaches that contribute to a paradigm-shift in distributed data mining by addressing most challenging issues related to Big Data, such as data sparsity, horizontal scaling, and parallel computation.
NEMICO: Mining network data through cloud-based data mining techniques / Baralis E.; Cagliero L.; Cerquitelli T.; Chiusano S.; Garza P.; Grimaudo L.; Pulvirenti F.. - (2014), pp. 503-504. ((Intervento presentato al convegno 7th International Conference on Utility and Cloud Computing (UCC 2014) tenutosi a Londra, Regno Unito nel 8-11 Dicembre 2014 [10.1109/UCC.2014.72].
| Titolo: | NEMICO: Mining network data through cloud-based data mining techniques | |
| Autori: | ||
| Data di pubblicazione: | 2014 | |
| Abstract: | Thanks to the rapid advances in Internet-based applications, data acquisition and storage technologies, petabyte-sized network data collections are becoming more and more common, thus prompting the need for scalable data analysis solutions. By leveraging today’s ubiquitous many-core computer architectures and the increasingly popular cloud computing paradigm, the applicability of data mining algorithms to these large volumes of network data can be scaled up to gain interesting insights. This paper proposes NEMICO, a comprehensive Big Data mining system targeted to network traffic flow analyses (e.g., traffic flow characterization, anomaly detection, multiplelevel pattern mining). NEMICO comprises new approaches that contribute to a paradigm-shift in distributed data mining by addressing most challenging issues related to Big Data, such as data sparsity, horizontal scaling, and parallel computation. | |
| Appare nelle tipologie: | 4.3 Poster |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| PosterUCC14.pdf | 1. Preprint / submitted version [pre- review] | PUBBLICO - Tutti i diritti riservati | Visibile a tuttiVisualizza/Apri |
http://hdl.handle.net/11583/2573940
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