NEMICO: Mining network data through cloud-based data mining techniques

被引:0
|
作者
Baralis, Elena [1 ]
Cagliero, Luca [1 ]
Cerquitelli, Tania [1 ]
Chiusano, Silvia [1 ]
Garza, Paolo [1 ]
Grimaudo, Luigi [1 ]
Pulvirenti, Fabio [1 ]
机构
[1] Politecn Torino, Dipartimento Automat & Informat, Turin, Italy
关键词
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中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Thanks to the rapid advances in Internet-based applications, data acquisition and storage technologies, petabyte-siwzed 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, multiple-level 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.
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收藏
页码:503 / 504
页数:2
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