M
Mohsen Guizani
Researcher at Qatar University
Publications - 1337
Citations - 48275
Mohsen Guizani is an academic researcher from Qatar University. The author has contributed to research in topics: Computer science & Cloud computing. The author has an hindex of 79, co-authored 1110 publications receiving 31282 citations. Previous affiliations of Mohsen Guizani include Jaypee Institute of Information Technology & University College for Women.
Papers
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KCLP: A k-Means Cluster-Based Location Privacy Protection Scheme in WSNs for IoT
TL;DR: This article proposes a k-means cluster-based location privacy (KCLP) protection scheme for IoT, which can increase the safety time and reduce delay at minor expense in energy consumption.
Posted Content
BPDS: A Blockchain based Privacy-Preserving Data Sharing for Electronic Medical Records
TL;DR: Security analysis shows that BPDS is a secure and effective way to realize data sharing for EMRs, which can be accomplished automatically according to the predefined access permissions of patients through the smart contracts of blockchain.
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Opportunistic Bandwidth Sharing Through Reinforcement Learning
TL;DR: A machine-learning-based scheme that will exploit the cognitive radios' capabilities to enable effective OSA, thus improving the efficiency of spectrum utilization and achieving high performance by learning from interaction with the environment.
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A Survey on Mobile Crowd-Sensing and Its Applications in the IoT Era
Khalid Abualsaud,Tarek Elfouly,Tamer Khattab,Elias Yaacoub,Loay Ismail,Mohamed H. Ahmed,Mohsen Guizani +6 more
TL;DR: The aim of this paper is to identify and explore the new paradigm of MCS that is using smartphone for capturing and sharing the sensed data between many nodes and discusses the current challenges facing the collection methodologies of the participants’ data in task management.
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Sustainability of Healthcare Data Analysis IoT-based Systems using Deep Federated Learning
TL;DR: Results collected show that the DFL models can preserve data privacy without sharing it, maintain the decentralized structure of the system made by IoT devices, improve the area under the curve (AUC) of the model to reach 97%, and reduce the operational costs (OC) for service providers.