A deep learning approach for network intrusion detection using a small features vector
H Ghani, B Virdee, S Salekzamankhani - Journal of Cybersecurity and …, 2023 - mdpi.com
With the growth in network usage, there has been a corresponding growth in the nefarious
exploitation of this technology. A wide array of techniques is now available that can be used …
exploitation of this technology. A wide array of techniques is now available that can be used …
Leveraging OPTUNA for hyperparameter tuning in GANS: a novel solution for class imbalance in IoT datasets
M Mouiti, A El Hariri, M Lazaar - Engineering Research Express, 2024 - iopscience.iop.org
Abstract The Internet of Things (IoT) has become more prevalent in recent years, generating
a huge amount of data from several interconnected devices. These datasets frequently …
a huge amount of data from several interconnected devices. These datasets frequently …
Evaluating the efficacy of decision tree-based machine learning in classifying intrusive behaviour of network users
A Panigrahi, MR Patra - International Journal of Advanced …, 2024 - search.proquest.com
Building network intrusion detection models to detect intrusive behaviour of malicious users
has been a major challenge to protect network resources. In this study, decision tree (DT) …
has been a major challenge to protect network resources. In this study, decision tree (DT) …
NIDS-ML-PSO: Network Intrusion Detection System based on Machine Learning Classifiers and Particle Swarm Optimization
WG Mahdi, DA Hammood, LH Abed… - Journal of Al-Qadisiyah …, 2024 - jqcsm.qu.edu.iq
As cyber threats continue to escalate with the rapid growth of internet usage, robust intrusion
detection systems (IDSs) are essential for safeguarding network infrastructures. This study …
detection systems (IDSs) are essential for safeguarding network infrastructures. This study …