Posts by Collection

How to Create Cooja Simulator Executable File on ContikiOS 3.0

Learn the quick steps to create an executable file for the Cooja simulator in ContikiOS 3.0, simplifying your development workflow on Linux.

Malicious Nodes Detection based on Artificial Neural Network in IoT Environments

Published in 2019 22nd International Conference on Computer and Information Technology (ICCIT), 2019

This study employs the Artificial Neural Network (ANN) to detect malicious nodes in IoT environments, addressing security concerns of embedded devices. The method discerns usual and malicious patterns, achieving a detection accuracy of 77.51%.

Recommended citation: M. A. Khatun, N. Chowdhury and M. N. Uddin, "Malicious Nodes Detection based on Artificial Neural Network in IoT Environments," 2019 22nd International Conference on Computer and Information Technology (ICCIT), Dhaka, Bangladesh, 2019, pp. 1-6, doi: 10.1109/ICCIT48885.2019.9038563. https://ieeexplore.ieee.org/document/9038563

Development of Cyber Attack Model for Private Network

Published in 2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS), 2022

This paper delves into the development and intricacies of a cyber attack model tailored for private networks.

Recommended citation: M. Al-Amin, M. A. Khatun and M. Nasir Uddin, 'Development of Cyber Attack Model for Private Network,' 2022 Second International Conference on Interdisciplinary Cyber Physical Systems (ICPS), Chennai, India, 2022, pp. 216-221, doi: 10.1109/ICPS55917.2022.00046. https://ieeexplore.ieee.org/abstract/document/9941250

Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation

Published in IEEE Access, 2023

This paper reviews and proposes risk mitigation strategies for security concerns in Healthcare-IoT systems using machine learning techniques.

Recommended citation: Mirza Akhi Khatun, Sanober Farheen Memon, Ciarán Eising, Lubna Luxmi Dhirani. (2023). "Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation." IEEE Access. 11. https://www.researchgate.net/publication/376763490_Machine_Learning_for_Healthcare-IoT_Security_A_Review_and_Risk_Mitigation

Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT

Published in 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI), USA, 2024

This research develops a novel method utilizing Convolutional Neural Networks (CNNs) to detect anomalies in time series data from environmental sensors within Healthcare-IoT systems.

Recommended citation: Khatun, M. A., Bhattacharya, M., Eising, C., & Dhirani, L. L. (2024). "Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT." 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI). https://arxiv.org/pdf/2407.20695

TCN-Based DDoS Detection and Mitigation in 5G Healthcare-IoT: A Frequency Monitoring and Dynamic Threshold Approach

Published in IEEE Access, 2025

This research presents a monitoring frequency-based detection and dynamic threshold mitigation method using Temporal Convolutional Networks (TCNs) in 5G Healthcare-IoT environments.

Recommended citation: Mirza Akhi, Ciarán Eising, and Lubna Luxmi Dhirani. (2025). "TCN-Based DDoS Detection and Mitigation in 5G Healthcare-IoT: A Frequency Monitoring and Dynamic Threshold Approach." IEEE Access. https://ieeexplore.ieee.org/iel8/6287639/6514899/10845749.pdf

Securing Healthcare-IoT using AI/ML

Published: November 09, 2023

Description:

The pandemic has demonstrated the need and role of a digitally transformed healthcare system (Healthcare 5.0). The biggest challenge in healthcare IoT (H-IoT) is security, as it connects medical devices, wearables, and infrastructure, enabling real-time monitoring and data sharing. As H-IoT devices transmit massive amounts of healthcare information every millisecond, privacy and security are of utmost importance. The increasing number, scale, and types of cyberattacks on healthcare facilities have demonstrated the urgency for new methods to secure the environment. This talk sheds light on securing H-IoT using AI/ML techniques protecting sensitive/healthcare data and ensuring medical device integrity. It also covers real-time threat and anomaly detection using ML algorithms.

Science Mathematics 2

Graduate Teaching Assistant, Department of Mathematics and Statistics, University of Limerick, 2023

Delivered one-hour lectures four times per week to the undergraduate students. Teaching Geometry, Trigonometry, Pre-Calculus, Calculus. Preparing and delivering lectures, and tutorials.

CE4051 - INTRODUCTION TO DATA ENGINEERING AND MACHINE LEARNING

Masters Program Teaching Assistant, Department of Electronic and Computer Engineering, University of Limerick, 2023

My responsibilities as a Teaching Assistant for the Masters program involved evaluating student activities in the area of machine learning meticulously. In particular, I assessed their understanding and application of key algorithms such as SVM, Perceptron, and Adaline, as well as their proficiency with tools such as Scikit-learn. Using rigorous feedback and objective marking, I sought to ensure that students not only understood theoretical concepts but were also able to put them into practice. I enjoyed this challenging role, which underscored the importance of providing students with a thorough assessment process in order to guide them in the right direction.

CE4317 - INTRODUCTION TO DATA ENGINEERING AND MACHINE LEARNING

Graduate Teaching Assistant, Department of Electronic and Computer Engineering, University of Limerick, 2023

Assisting with an ongoing undergraduate course as a teaching assistant that delves into probability distributions, the Naive Bayes classifier, among other emerging algorithms.