S
Shukor Abd Razak
Researcher at Universiti Teknologi Malaysia
Publications - 145
Citations - 1777
Shukor Abd Razak is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: Wireless sensor network & Network packet. The author has an hindex of 19, co-authored 133 publications receiving 1349 citations. Previous affiliations of Shukor Abd Razak include University of Plymouth.
Papers
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Journal ArticleDOI
Interference-Aware Multipath Routing Protocol for QoS Improvement in Event-Driven Wireless Sensor Networks
Marjan Radi,Behnam Dezfouli,Kamalrulnizam Abu Bakar,Shukor Abd Razak,Mohammad Ali Nematbakhsh +4 more
TL;DR: This paper proposes a Low- Interference Energy-efficient Multipath Routing protocol (LIEMRO) to improve the QoS requirements of event-driven applications and employs a quality-based load balancing algorithm to regulate the amount of traffic injected into the paths.
Journal ArticleDOI
Modeling low-power wireless communications
TL;DR: This is the first work that reveals the essentials of accurate modeling and evaluation of low-power wireless communications and shows that the transitional region can be employed by the simulators to confine the propagation range and improve simulation scalability.
Journal ArticleDOI
An overview of data routing approaches for wireless sensor networks.
TL;DR: The main goals of data routing approach in sensor networks are described, and the best known and most recent data routing approaches in WSNs are classified and studied according to their specific goals.
Proceedings ArticleDOI
LIEMRO: A Low-Interference Energy-Efficient Multipath Routing Protocol for Improving QoS in Event-Based Wireless Sensor Networks
TL;DR: Simulation results show that using LIEMRO in high traffic load conditions can increase data reception rate and network lifetime even more than 1.5x compared with single path routing approach, while end-to-end latency reduces significantly.
Journal ArticleDOI
Anomaly-Based Intrusion Detection Systems in IoT Using Deep Learning: A Systematic Literature Review
Muaadh A. Alsoufi,Shukor Abd Razak,Maheyzah Md Siraj,Ibtehal Nafea,Fuad A. Ghaleb,Faisal Saeed,Maged Nasser +6 more
TL;DR: A systematic literature review is presented to analyze the existing published literature regarding anomaly-based intrusion detection, using deep learning techniques in securing IoT environments and finds that supervised deep learning Techniques offer better performance, compared to unsupervised and semi-supervised learning.