XGBoost for IDS on WSN Cyber Attacks with Imbalanced Data-Reference-Cited by-同舟云学术

XGBoost for IDS on WSN Cyber Attacks with Imbalanced Data

Published:2022-11-08 Issue: Volume: Page:
ISSN:
Container-title:2022 International Symposium on Electronics and Smart Devices (ISESD)
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Author:

Putrada Aji Gautama¹,Alamsyah Nur¹,Pane Syafrial Fachri¹,Fauzan Mohamad Nurkamal¹

Affiliation:

1. Telkom University,Advanced and Creative Networks Research Center,Bandung,Indonesia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9980473/9980545/09980630.pdf?arnumber=9980630

Reference33 articles.

1. An online ensemble learning model for detecting attacks in wireless sensor networks;tabbaa;arXiv preprint arXiv 2204 13814,2022

2. An effective classification for dos attacks in wireless sensor networks;park;2018 Tenth International Conference on Ubiquitous and Future Networks (ICUFN),2018

3. A Genetic-Based Extreme Gradient Boosting Model for Detecting Intrusions in Wireless Sensor Networks

4. A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU

5. I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems

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