A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space

Huong, Truong Thu and Bac, Ta Phuong and Nguyen, Quoc Thong and Nguyen, Huu Du and Tran, Kim Phuc (2019) A data-driven approach for Network Intrusion Detection and Monitoring based on Kernel Null Space. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 6 (20): 1. ISSN 2410-0218

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Abstract

In this study, we propose a new approach to determine intrusions of network in real-time based on statistical process control technique and kernel null space method. The training samples in a class are mapped to a single point using the Kernel Null Foley-Sammon Transform. The Novelty Score are computed from testing samples in order to determine the threshold for the real-time detection of anomaly. The efficiency of the proposed method is illustrated over the KDD99 data set. The experimental results show that our new method outperforms the OCSVM and the original Kernel Null Space method by 1.53% and 3.86% respectively in terms of accuracy.

Item Type:	Article
Uncontrolled Keywords:	Network Security Support, Kernel Quantile Estimator, One-class Classification, Kernel Null Space vector machine
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science QA75 Electronic computers. Computer science
Depositing User:	EAI Editor I.
Date Deposited:	11 Sep 2020 08:54
Last Modified:	11 Sep 2020 08:54
URI:	https://eprints.eudl.eu/id/eprint/255

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