Journal ArticleOpen Access
IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model
Author Affiliations
Chittagong University of Engineering & Technology, Swinburne University of Technology, King Abdulaziz University
Published InSymmetry
Year2020
Citations323
Abstract
Cyber security has recently received enormous attention in today’s security concerns, due to the popularity of the Internet-of-Things (IoT), the tremendous growth of computer networks, and the huge number of relevant applications. Thus, detecting various cyber-attacks or anomalies in a network and building an effective intrusion detection system that performs an essential role in today’s security is becoming more important. Artificial intelligence, particularly machine learning techniques, can be used for building such a data-driven intelligent intrusion detection system. In order to achieve this goal, in this paper, we present an Intrusion Detection Tree (“IntruDTree”) machine-learning-based security model that first takes into account the ranking of security features according to their importance and then build a tree-based generalized intrusion detection model…
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