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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.

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Proceedings ArticleDOI

A Secure, Lightweight, and Privacy-Preserving Authentication Scheme for V2G Connections in Smart Grid

TL;DR: An Elliptic Curve Cryptography-based privacy preserving scheme for V2G networks, which enables data sharing while maintaining the required level of security and validation of the efficacy of the proposed scheme in imparting high security features with limited overhead is proposed.
Journal ArticleDOI

Predictive analysis in outpatients assisted by the Internet of Medical Things

TL;DR: The results of the comparative experiments show that the outpatient quantity prediction is not a simple time-series problem, and it contains a variety of nonlinear influencing factors, so the multi-dimensional prediction model including air quality feature is better than others, and the experimental results prove that air quality indicators play an important role in the prediction of respiratory clinic outpatient visits.
Proceedings ArticleDOI

A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing

TL;DR: In this article, the authors proposed an efficient and lightweight mutual authentication protocol for MEC environments; based on Elliptic Curve Cryptography (ECC), one-way hash functions and concatenation operations.
Journal ArticleDOI

Adaptive DE Algorithm for Novel Energy Control Framework Based on Edge Computing in IIoT Applications

TL;DR: This article proposes a highly efficient energy control framework supported by edge computing to reduce energy waste and increase the benefit for industrial users, and proposes an adaptive mixed differential evolution algorithm with a novel mutation strategy.
Proceedings ArticleDOI

Traffic Analysis Attacks on Tor: A Survey

TL;DR: This study examines traffic analysis attacks from the perspective of the adopted adversary model and how much it fits within Tor's threat model to evaluate how practical these attacks are on real-time Tor network.