Citation
Mozo Velasco, Bonifacio Alberto and Zhu, Bo
(2014).
A survey of feature selection in Internet traffic characterization.
In: "First International Workshop on Big Data Applications and Principles", 11/09/2014 - 12/09/2014, Madrid, España. ISBN 978-84-15302-94-0. pp. 69-88.
Abstract
In the last decade, the research community has focused on new classification methods that rely on statistical characteristics of Internet traffic, instead of pre-viously popular port-number-based or payload-based methods, which are under even bigger constrictions. Some research works based on statistical characteristics generated large fea-ture sets of Internet traffic; however, nowadays it?s impossible to handle hun-dreds of features in big data scenarios, only leading to unacceptable processing time and misleading classification results due to redundant and correlative data. As a consequence, a feature selection procedure is essential in the process of Internet traffic characterization. In this paper a survey of feature selection methods is presented: feature selection frameworks are introduced, and differ-ent categories of methods are briefly explained and compared; several proposals on feature selection in Internet traffic characterization are shown; finally, future application of feature selection to a concrete project is proposed.