Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

no code implementations • 22 Jan 2024 • Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin, Khondokar Fida Hasan, Selina Sharmin, Salem A. Alyami, Mohammad Ali Moni

Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activities.

Blocking Dimensionality Reduction +1

An Optimized Ensemble Deep Learning Model For Brain Tumor Classification

no code implementations • 22 May 2023 • Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin

Experimentation is conducted on the Figshare Contrast-Enhanced MRI (CE-MRI) brain tumor dataset, comprising 3064 images.

Transfer Learning

A Dependable Hybrid Machine Learning Model for Network Intrusion Detection

no code implementations • 8 Dec 2022 • Md. Alamin Talukder, Khondokar Fida Hasan, Md. Manowarul Islam, Md Ashraf Uddin, Arnisha Akhter, Mohammad Abu Yousuf, Fares Alharbi, Mohammad Ali Moni

Network intrusion detection systems (NIDSs) play an important role in computer network security.

feature selection Network Intrusion Detection

Machine Learning-based Lung and Colon Cancer Detection using Deep Feature Extraction and Ensemble Learning

no code implementations • 2 Jun 2022 • Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin, Arnisha Akhter, Khondokar Fida Hasan, Mohammad Ali Moni

The model is evaluated on histopathological (LC25000) lung and colon datasets.

Ensemble Learning