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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Book ChapterDOI
Secure medical treatment with deep learning on embedded board
TL;DR: This chapter designs a complete prototype of an embedded system for the prediction of different attack patterns in deep brain stimulation (DBS) to mitigate intrusions to such critical devices and proves the robustness of the proposed device by emulating several random attacks on the stimulator.
Posted Content
PPLS: A Privacy-Preserving Location-Sharing Scheme in Vehicular Social Networks.
TL;DR: This paper proposes a PRivacy-preserving Interest-based Forwarding scheme (PRIF) for SIOV, which not only protects the interest information, but also improves the forwarding performance, and proposes a privacy-preserve authentication protocol to recognize communities among mobile nodes.
Proceedings ArticleDOI
A Machine Learning Approach of Load Balance Routing to Support Next-Generation Wireless Networks
TL;DR: A load balance routing algorithm considering Queue Utilization (QU) is designed and a neural network is used for the prediction of the network queue status, which can be used as a metric for making intelligent routing decisions.
Journal ArticleDOI
Congestion Game With Link Failures for Network Selection in High-Speed Vehicular Networks
TL;DR: The results demonstrate that E-CGF outperforms others by alleviating network congestion and improving transmission reliability with a moderate trade-off between achieved throughput and transit cost.
Proceedings ArticleDOI
Smart Edge Healthcare Data Sharing System
TL;DR: A new healthcare system to reduce the waiting time in emergency department and improve the network scalability in any distributed system that integrates the power of edge computing with machine learning techniques for providing a good quality of healthcare services is proposed.