Performance Comparison of IoT Classification Models using Ensemble Stacking and Feature Importance
Internet of Things (IoT) security is becoming a top priority as the number of connected devices increases online. This research utilizes the CIC IoT ATTACK 2023 dataset from the University of Brunswick, which consists of 46 million data on various types of attacks on IoT devices, such as DDoS, DoS,...
Saved in:
Main Authors: | nabila putri setiawan, Adhitya Nugraha, Ardytha Luthfiarta, Yudha Mulyana |
---|---|
Format: | Article |
Language: | Indonesian |
Published: |
Islamic University of Indragiri
2024-11-01
|
Series: | Sistemasi: Jurnal Sistem Informasi |
Online Access: | https://sistemasi.ftik.unisi.ac.id/index.php/stmsi/article/view/4673 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Motor Imagery EEG Classification Based on Multi-Domain Feature Rotation and Stacking Ensemble
by: Xianglong Zhu, et al.
Published: (2025-01-01) -
An Ensemble Learning Based Intrusion Detection Model for Industrial IoT Security
by: Mouaad Mohy-Eddine, et al.
Published: (2023-09-01) -
Sistem Monitoring Trafo Distribusi PT.PLN (Persero) berbasis IoT
by: Budi Eko Prasetyo, et al.
Published: (2020-02-01) -
Cutting-Edge Intrusion Detection in IoT Networks: A Focus on Ensemble Models
by: Najm Us Sama, et al.
Published: (2025-01-01) -
Chaos Game Optimization with stacked LSTM sequence to sequence autoencoder for malware detection in IoT cloud environment
by: Moneerah Alotaibi, et al.
Published: (2025-01-01)