IEEE Future Networks World Forum
12-14 October 2022 | Montreal, Canada + Virtual (Hybrid)

WS2: Workshop on Artificial Intelligence (AI)-Enabled Future Networks: A Cross-layer Perspective

14 October 2022 // 14:00 – 15:30 // Virtual



The demand for Data Transfer Rate is rising due to the increase of Data Traffic over time, which urges us to enhance the network systems capabilities from 4G to 5G. However, recently these demands have increased exponentially, and we need to develop a more robust physical network infrastructure to ensure enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), massive Machine Type Communications (mMTC), and security with dynamic, adaptive, and self-learning AI systems for upcoming Beyond 5G (B5G) and 6G.

B5G and 6G may bring enormous challenges because of several aspects, such as superior sensitivity, spectrum management, architectural design, network complexity, heterogeneity enhancement, trustworthiness, resource management, application possibilities, energy management, etc. Consequently, it is essential to develop a robust pathway exploiting currently available facilities, physical networks instrument, devices, Cross-layering aspects, and AI techniques to ensure a sustainable B5G/6G for the future. Therefore, we aim to organize a workshop on AI-enabled Future Networks: A Cross-layer Perspective, where the respected academician, researcher, entrepreneur, industrial practitioners, governmental agencies, and many others may share their innovations, individual thoughts, propositions, latest finding, technical challenges, open research scope, potential application scope, solutions as theories, algorithms, key technologies and so on.


A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless NetworksMurat Kuzlu (Old Dominion University, USA); Ferhat Ozgur Catak (University of Stavanger, Norway); Salih Sarp (Virginia Commonwealth University & Old Dominion University, USA); Umit Cali (NTNU, USA); Oezguer Gueler (Old Dominion University, USA)

Cloud Native Applications Profiling using a Graph Neural Networks ApproachAmine Boukhtouta (Ericsson Research, Canada); Taous Madi (King Abdullah University of Science and Technology, Saudi Arabia); Makan Pourzandi (Ericsson, Canada); Hyame Alameddine (Ericsson Research, Canada) // (Note: This paper has been scheduled in workshop WS5, on-site presentation click here)

Business Models for 5G and Future Mobile Network OperatorsLaurence Banda and Mjumo Mzyece (University of the Witwatersrand, South Africa); Fisseha Mekuria (Malmo University, Sweden & Technology & Society, Sweden)

Attack Graphs for Standalone Non-Public 5G Networks – Arpit Tripathi (Indian Institute of Technology Hyderabad & Institute for Development and Research in Banking Technology, India); Abhishek Thakur (IDRBT, India); Bheemarjuna Reddy Tamma (IIT Hyderabad, India)

On Securing MAC Layer Broadcast Signals Against Covert Channel Exploitation in 5G, 6G & Beyond Reza S Soosahabi (University of Louisiana Lafayette & Keysight Technologies, USA); Magdy A Bayoumi (University of Louisiana Lafayette, USA)

An Innovative Hashgraph-based Federated Learning Approach for 5G Network ProtectionHisham A. Kholidy (State University of New York (SUNY) Polytechnic Institute, USA); Riaad Kamaludeen (SUNY Polytechnic Institute, USA)

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