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Imtiaz Ullah
Researcher at University of Ontario Institute of Technology
Publications - 11
Citations - 461
Imtiaz Ullah is an academic researcher from University of Ontario Institute of Technology. The author has contributed to research in topics: Intrusion detection system & F1 score. The author has an hindex of 6, co-authored 9 publications receiving 133 citations.
Papers
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Journal ArticleDOI
Design and Development of a Deep Learning-Based Model for Anomaly Detection in IoT Networks
Imtiaz Ullah,Qusay H. Mahmoud +1 more
TL;DR: In this article, a novel anomaly-based IDS (Intrusion Detection System) using machine learning techniques to detect and classify attacks in IoT networks is proposed, where a convolutional neural network model is used to create a multiclass classification model.
Book ChapterDOI
A Scheme for Generating a Dataset for Anomalous Activity Detection in IoT Networks
Imtiaz Ullah,Qusay H. Mahmoud +1 more
TL;DR: The weaknesses of various intrusion detection datasets are reviewed and a new dataset namely IoTID20 generated dataset is proposed, which will provide a foundation for the development of new intrusion detection techniques in IoT networks.
Journal ArticleDOI
A Two-Level Flow-Based Anomalous Activity Detection System for IoT Networks
Imtiaz Ullah,Qusay H. Mahmoud +1 more
TL;DR: A two-level anomalous activity detection model for intrusion detection system in IoT networks will provide a robust framework for the development of malicious activity detection system for IoT networks and would be of interest to researchers in academia and industry.
Proceedings ArticleDOI
A hybrid model for anomaly-based intrusion detection in SCADA networks
Imtiaz Ullah,Qusay H. Mahmoud +1 more
TL;DR: The experimental results show that the proposed hybrid model for anomaly-based intrusion detection in SCADA networks has a key effect in reducing the time and computational complexity and achieved improved accuracy and detection rate.
Proceedings ArticleDOI
A Two-Level Hybrid Model for Anomalous Activity Detection in IoT Networks
Imtiaz Ullah,Qusay H. Mahmoud +1 more
TL;DR: The predictor the authors introduce in this paper provides a solid framework for the development of malicious activity detection in IoT networks.