Universal Feature Extraction for Traffic Identification of the Target Category.

ABSTRACT: Traffic identification of the target category is currently a significant challenge for network monitoring and management. To identify the target category with pertinence, a feature extraction algorithm based on the subset with highest proportion is presented in this paper. The method is proposed to be applied to the identification of any category that is assigned as the target one, but not restricted to certain specific category. We divide the process of feature extraction into two stages. In the stage of primary feature extraction, the feature subset is extracted from the dataset which has the highest proportion of the target category. In the stage of secondary feature extraction, the features that can distinguish the target and interfering categories are added to the feature subset. Our

SUBMITTER: Shen J 

PROVIDER: S-EPMC5104389 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature