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Miss Laiha Mat Kiah

Researcher at Information Technology University

Publications -  125
Citations -  4821

Miss Laiha Mat Kiah is an academic researcher from Information Technology University. The author has contributed to research in topics: Computer science & Adaptive neuro fuzzy inference system. The author has an hindex of 36, co-authored 113 publications receiving 3975 citations. Previous affiliations of Miss Laiha Mat Kiah include University of Malaya.

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A review of smart home applications based on Internet of Things

TL;DR: A review is conducted to map the research landscape of smart home based on Internet of Things into a coherent taxonomy and identifies the basic characteristics of this emerging field in the following aspects: motivation of using IoT in smart home applications, open challenges hindering utilization, and recommendations to improve the acceptance and use of smartHome IoT applications in literature.
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Towards secure mobile cloud computing: A survey

TL;DR: This literature review highlights the current state of the art work proposed to secure mobile cloud computing infrastructures, identifies the potential problems, and provides a taxonomy of the state-of-the- art.
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Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission

TL;DR: In this paper, an adaptive neuro-fuzzy inference system (ANFIS) based controller for variable-speed operation of a wind turbine was proposed to improve the wind energy available in an erratic wind speed regime.
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On cloud security attacks

TL;DR: This research work presents taxonomy of cloud security attacks and potential mitigation strategies with the aim of providing an in-depth understanding of security requirements in the cloud environment and highlights the importance of intrusion detection and prevention as a service.
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Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks

TL;DR: The proposed cooperative Game-based Fuzzy Q-learning (G-FQL) model implements cooperative defense counter-attack scenarios for the sink node and the base station to operate as rational decision-maker players through a game theory strategy, and yields a greater improvement than existing machine learning methods.