Hybrid Feature Selection Framework for Building Resource Efficient Intrusion Detection Systems Model in the Internet of Things-Reference-Cited by-同舟云学术

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Hybrid Feature Selection Framework for Building Resource Efficient Intrusion Detection Systems Model in the Internet of Things

Published:2023-10-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology
language:
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Author:

Fatyanosa Tirana Noor¹^ORCID,Data Mahendra¹^ORCID

Affiliation:

1. Universitas Brawijaya, Indonesia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626641.3626923

Reference14 articles.

1. Ahmad Alsahaf , George Azzopardi , Bart Ducro , Roel F Veerkamp , and Nicolai Petkov . 2018. Predicting Slaughter Weight in Pigs with Regression Tree Ensembles . In Applications of Intelligent Systems . IOS Press , Amsterdam , 1–9. Ahmad Alsahaf, George Azzopardi, Bart Ducro, Roel F Veerkamp, and Nicolai Petkov. 2018. Predicting Slaughter Weight in Pigs with Regression Tree Ensembles. In Applications of Intelligent Systems. IOS Press, Amsterdam, 1–9.

2. A framework for feature selection through boosting

3. XGBoost

4. An Incremental Learning Algorithm on Imbalanced Data for Network Intrusion Detection Systems

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