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
More filters
Journal ArticleDOI
High-speed protocol for an all-optical packet switched metropolitan area network
TL;DR: An optical metropolitan area network employing packet switching and wavelength division multi-accessing is discussed in this article and two variations are presented.
Journal ArticleDOI
Virtual-Link Relay Selection Scheme for Buffer-Aided IoT Based Cooperative Relay Networks
TL;DR: This paper investigates the performance of a buffer-aided cooperative relay network and derives the closed-form expressions for outage probability, diversity gain, delay, and throughput for symmetric and asymmetric channel conditions.
Proceedings ArticleDOI
Spatiotemporal Location Differential Privacy for Sparse Mobile Crowdsensing
TL;DR: Wang et al. as discussed by the authors combine spatio-temporal activity privacy with location differential privacy and propose a novel location privacy-preserving mechanism, which is within the acceptable error range of 10-3∼10-2, which can achieve more comprehensive and stronger location privacy.
Proceedings ArticleDOI
Deep Learning and Blockchain-based Framework to Detect Malware in Autonomous Vehicles
Dev Dineshkumar Patel,Dhairya Jadav,Rajesh Gupta,Nilesh Jadav,Sudeep Tanwar,Bassem Ouni,Mohsen Guizani +6 more
TL;DR: A Deep Learning (DL) and Blockchain framework is proposed for AV to resolve security challenges and proves to be efficient in detecting malware with an accuracy of 97.56%.
Proceedings ArticleDOI
A Non-Intrusive Method for Smart Speaker Forensics
TL;DR: Wang et al. as discussed by the authors proposed a non-intrusive digital forensic method for smart speakers, which combines network traffic analysis with the extraction of user intent and alarms about abnormal network traffic to support the investigation of security.