The Hierarchical Ensemble Model for Network Intrusion Detection in the Real-world Dataset

Lei Chen, Shao En Weng, Chu Jun Peng, Yin Chi Li, Hong Han Shuai, Wen Huang Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Network intrusion detection is an indispensable defense in the critical era fulling of cyberattacks. However, it faces a severe class imbalanced issue, and most of the researches are conducted on simulated data. Therefore, this work introduces a hierarchical ensemble architecture with machine learning approaches. It is trained on the latest and real-world dataset to solve the above problems. The experiments show that we outperform state-of-the-art methods on real network traffic data.

Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems, ISCAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2983-2987
Number of pages5
ISBN (Electronic)9781665484855
DOIs
StatePublished - 2022
Event2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 - Austin, United States
Duration: 27 May 20221 Jun 2022

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2022-May
ISSN (Print)0271-4310

Conference

Conference2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
Country/TerritoryUnited States
CityAustin
Period27/05/221/06/22

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