An Empirical Evaluation of Supervised Learning Methods for Network Malware Identification Based on Feature Selection

An Empirical Evaluation of Supervised Learning Methods for Network Malware Identification Based on Feature Selection

Malware is a sophisticated, malicious, and sometimes unidentifiable application on the network. The classifying network traffic method using machine learning shows to perform well in detecting malware. In the literature, it is reported that this good performance can depend on a reduced set of networ...

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Bibliographic Details
Main Authors:	C. Manzano, C. Meneses, P. Leger, H. Fukuda
Format:	Article
Language:	English
Published:	Wiley 2022-01-01
Series:	Complexity
Online Access:	http://dx.doi.org/10.1155/2022/6760920
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