A stacking ensemble of deep learning models for IoT intrusion detection

Author:

Lazzarini RiccardoORCID,Tianfield HuagloryORCID,Charissis VassilisORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference72 articles.

1. A review on machine learning and deep learning perspectives of IDS for IoT: Recent updates, security issues, and challenges;Thakkar;Arch. Comput. Methods Eng.,2021

2. Machine-learning methods for computational science and engineering;Frank;MDPI Comput.,2020

3. A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges;Khraisat;Cybersecurity,2021

4. Intelligent techniques for detecting network attacks: Review and research directions;Aljabri,2021

5. A survey of deep learning methods for cyber security;Berman;Information (Switzerland),2019

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1. M2VT-IDS: A multi-task multi-view learning architecture for designing IoT intrusion detection system;Internet of Things;2024-04

2. Enhancing IoT Attack Detection Through Ensemble-Based Multiclass Attacks Classification;2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET);2023-12-04

3. Logistic Regression Ensemble Classifier for Intrusion Detection System in Internet of Things;Sensors;2023-12-03

4. A Three-layer Convolution Neural Network Approach for Intrusion Detection in IoT;2023 Eleventh International Conference on Intelligent Computing and Information Systems (ICICIS);2023-11-21

5. IoT Intrusion Detection System Based on Machine Learning;Electronics;2023-10-17

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