文章基本信息

标题：Machine Learning in Network Security Using KNIME Analytics
本地全文：下载
作者：Munther Abualkibash
期刊名称：International Journal of Network Security & Its Applications
印刷版ISSN：0975-2307
电子版ISSN：0974-9330
出版年度：2019
卷号：11
期号：5
页码：1-14
DOI：10.5121/ijnsa.2019.11501
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Machine learning has more and more effect on our every day’s life. This field keeps growing and expanding into new areas. Machine learning is based on the implementation of artificial intelligence that gives systems the capability to automatically learn and enhance from experiments without being explicitly programmed. Machine Learning algorithms apply mathematical equations to analyze datasets and predict values based on the dataset. In the field of cybersecurity, machine learning algorithms can be utilized to train and analyze the Intrusion Detection Systems (IDSs) on security-related datasets. In this paper, we tested different machine learning algorithms to analyze NSL-KDD dataset using KNIME analytics.
关键词：Network Security; KNIME; NSL;KDD; and Machine Learning