activity
20222024
most citedA Dependable Hybrid Machine Learning Model for Network Intrusion Detection

173 citations · 215 across the 13 of their papers we have counts for

collaborators

13 papers

eess.IV2024★ 2 cited

An Integrated Deep Learning Model for Skin Cancer Detection Using Hybrid Feature Fusion Technique

Maksuda Akter, Rabea Khatun, Md. Alamin Talukder +2

Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this grou…

cs.CR2024★ 2 cited

Hierarchical Classification for Intrusion Detection System: Effective Design and Empirical Analysis

Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek +2

With the increased use of network technologies like Internet of Things (IoT) in many real-world applications, new types of cyberattacks have been emerging. To safeguard critical in…

cs.CR2024

A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats

Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek +2

In today's digital age, our dependence on IoT (Internet of Things) and IIoT (Industrial IoT) systems has grown immensely, which facilitates sensitive activities such as banking tra…

cs.CR2024

usfAD Based Effective Unknown Attack Detection Focused IDS Framework

Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek +2

The rapid expansion of varied network systems, including the Internet of Things (IoT) and Industrial Internet of Things (IIoT), has led to an increasing range of cyber threats. Ens…

eess.IV2024★ 13 cited

Hybridized Convolutional Neural Networks and Long Short-Term Memory for Improved Alzheimer's Disease Diagnosis from MRI Scans

Maleka Khatun, Md Manowarul Islam, Habibur Rahman Rifat +3

Brain-related diseases are more sensitive than other diseases due to several factors, including the complexity of surgical procedures, high costs, and other challenges. Alzheimer's…

q-bio.GN2024★ 2 cited

Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma

Abanti Bhattacharjya, Md Manowarul Islam, Md Ashraf Uddin +7

With the advent of Information technology, the Bioinformatics research field is becoming increasingly attractive to researchers and academicians. The recent development of various…

cs.LG2024★ 4 cited

Securing Transactions: A Hybrid Dependable Ensemble Machine Learning Model using IHT-LR and Grid Search

Md. Alamin Talukder, Rakib Hossen, Md Ashraf Uddin +2

Financial institutions and businesses face an ongoing challenge from fraudulent transactions, prompting the need for effective detection methods. Detecting credit card fraud is cru…

cs.CR2024★ 1 cited

MLSTL-WSN: Machine Learning-based Intrusion Detection using SMOTETomek in WSNs

Md. Alamin Talukder, Selina Sharmin, Md Ashraf Uddin +2

Wireless Sensor Networks (WSNs) play a pivotal role as infrastructures, encompassing both stationary and mobile sensors. These sensors self-organize and establish multi-hop connect…

cs.CR2024★ 3 cited

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

Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin +4

Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors a…

eess.IV2023

Empowering COVID-19 Detection: Optimizing Performance Through Fine-Tuned EfficientNet Deep Learning Architecture

Md. Alamin Talukder, Md. Abu Layek, Mohsin Kazi +2

The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of individuals across the planet. It is a highly contagious respiratory disease requir…

eess.IV2023★ 3 cited

An Optimized Ensemble Deep Learning Model For Brain Tumor Classification

Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin

Brain tumors present a grave risk to human life, demanding precise and timely diagnosis for effective treatment. Inaccurate identification of brain tumors can significantly diminis…

cs.CR2023★ 173 cited

A Dependable Hybrid Machine Learning Model for Network Intrusion Detection

Md. Alamin Talukder, Khondokar Fida Hasan, Md. Manowarul Islam +5

Network intrusion detection systems (NIDSs) play an important role in computer network security. There are several detection mechanisms where anomaly-based automated detection outp…

eess.IV2022★ 12 cited

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

Md. Alamin Talukder, Md. Manowarul Islam, Md Ashraf Uddin +3

Cancer is a fatal disease caused by a combination of genetic diseases and a variety of biochemical abnormalities. Lung and colon cancer have emerged as two of the leading causes of…