99 citations · 219 across the 7 of their papers we have counts for
7 papers
FedSkipTwin: Digital-Twin-Guided Client Skipping for Communication-Efficient Federated Learning
Daniel Commey, Kamel Abbad, Garth V. Crosby +1
Communication overhead remains a primary bottleneck in federated learning (FL), particularly for applications involving mobile and IoT devices with constrained bandwidth. This work…
Deep Multimodal Learning for Real-Time DDoS Attacks Detection in Internet of Vehicles
Mohamed Ababsa, Soheyb Ribouh, Abdelhamid Malki +1
The progress and integration of intelligent transport systems (ITS) have therefore been central to creating safer and more efficient transport networks. The Internet of Vehicles (I…
An Overview of Blockchain and 5G Networks
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
The 5G wireless networks are potentially revolutionizing future technologies. The 5G technologies are expected to foresee demands of diverse vertical applications with diverse requ…
An IoT Blockchain Architecture Using Oracles and Smart Contracts: the Use-Case of a Food Supply Chain
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
The blockchain is a distributed technology which allows establishing trust among unreliable users who interact and perform transactions with each other. While blockchain technology…
Prediction and Detection of FDIA and DDoS Attacks in 5G Enabled IoT
Hajar Moudoud, Lyes Khoukhi, Soumaya Cherkaoui
Security in the fifth generation (5G) networks has become one of the prime concerns in the telecommunication industry. 5G security challenges come from the fact that 5G networks in…
Towards a Scalable and Trustworthy Blockchain: IoT Use Case
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
Recently, blockchain has gained momentum as a novel technology that gives rise to a plethora of new decentralized applications (e.g., Internet of Things (IoT)). However, its integr…
Towards a Secure and Reliable Federated Learning using Blockchain
Hajar Moudoud, Soumaya Cherkaoui, Lyes Khoukhi
Federated learning (FL) is a distributed machine learning (ML) technique that enables collaborative training in which devices perform learning using a local dataset while preservin…