Omar Abdel Wahab

Orcid: 0000-0002-3991-4673

Affiliations:
  • Polytechnique Montréal, Canada
  • Université du Québec en Outaouais, Gatineau, Canada (former)


According to our database1, Omar Abdel Wahab authored at least 57 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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PhD thesis 
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Online presence:

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Bibliography

2024
Trust-driven reinforcement selection strategy for federated learning on IoT devices.
Computing, April, 2024

2023
A Survey on Explainable Artificial Intelligence for Cybersecurity.
IEEE Trans. Netw. Serv. Manag., December, 2023

Deep learning-enabled anomaly detection for IoT systems.
Internet Things, April, 2023

A Survey on IoT Intrusion Detection: Federated Learning, Game Theory, Social Psychology, and Explainable AI as Future Directions.
IEEE Internet Things J., March, 2023

Coalitional Federated Learning: Improving Communication and Training on Non-IID Data With Selfish Clients.
IEEE Trans. Serv. Comput., 2023

FedMint: Intelligent Bilateral Client Selection in Federated Learning With Newcomer IoT Devices.
IEEE Internet Things J., 2023

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions.
CoRR, 2023

A Survey on Explainable Artificial Intelligence for Network Cybersecurity.
CoRR, 2023

Towards Mutual Trust-Based Matching For Federated Learning Client Selection.
Proceedings of the International Wireless Communications and Mobile Computing, 2023

Explainable Trust-aware Selection of Autonomous Vehicles Using LIME for One-Shot Federated Learning.
Proceedings of the International Wireless Communications and Mobile Computing, 2023

Towards Instant Clustering Approach for Federated Learning Client Selection.
Proceedings of the International Conference on Computing, Networking and Communications, 2023

A Max-Min Security Game for Coordinated Backdoor Attacks on Federated Learning.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Cloud Computing as a Platform for Monetizing Data Services: A Two-Sided Game Business Model.
IEEE Trans. Netw. Serv. Manag., 2022

Federated against the cold: A trust-based federated learning approach to counter the cold start problem in recommendation systems.
Inf. Sci., 2022

Intrusion Detection in the IoT Under Data and Concept Drifts: Online Deep Learning Approach.
IEEE Internet Things J., 2022

Explainable AI-based Federated Deep Reinforcement Learning for Trusted Autonomous Driving.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

Machine Learning Based Container Placement in On-Demand Clustered Fogs.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

Towards Bilateral Client Selection in Federated Learning Using Matching Game Theory.
Proceedings of the IEEE Global Communications Conference, 2022

One-Shot Federated Learning-based Model-Free Reinforcement Learning.
Proceedings of the International Conference on Deep Learning, 2022

2021
Protecting the Internet of Vehicles Against Advanced Persistent Threats: A Bayesian Stackelberg Game.
IEEE Trans. Reliab., 2021

Resource-Aware Detection and Defense System against Multi-Type Attacks in the Cloud: Repeated Bayesian Stackelberg Game.
IEEE Trans. Dependable Secur. Comput., 2021

Ad Hoc Vehicular Fog Enabling Cooperative Low-Latency Intrusion Detection.
IEEE Internet Things J., 2021

Trends, Politics, Sentiments, and Misinformation: Understanding People's Reactions to COVID-19 During its Early Stages.
CoRR, 2021

Deep and reinforcement learning for automated task scheduling in large-scale cloud computing systems.
Concurr. Comput. Pract. Exp., 2021

Federated Machine Learning: Survey, Multi-Level Classification, Desirable Criteria and Future Directions in Communication and Networking Systems.
IEEE Commun. Surv. Tutorials, 2021

Improving Autonomous Vehicles Safety in Snow Weather Using Federated YOLO CNN Learning.
Proceedings of the Mobile Web and Intelligent Information Systems, 2021

VirtualGAN: Reducing Mode Collapse in Generative Adversarial Networks Using Virtual Mapping.
Proceedings of the International Joint Conference on Neural Networks, 2021

Cloud as platform for monetizing complementary data for AI-driven services: A two-sided cooperative game.
Proceedings of the IEEE International Conference on Services Computing, 2021

2020
Optimal Load Distribution for the Detection of VM-Based DDoS Attacks in the Cloud.
IEEE Trans. Serv. Comput., 2020

FoGMatch: An Intelligent Multi-Criteria IoT-Fog Scheduling Approach Using Game Theory.
IEEE/ACM Trans. Netw., 2020

MuSC: A multi-stage service chains embedding approach.
J. Netw. Comput. Appl., 2020

An endorsement-based trust bootstrapping approach for newcomer cloud services.
Inf. Sci., 2020

Detection of time series patterns and periodicity of cloud computing workloads.
Future Gener. Comput. Syst., 2020

BigTrustScheduling: Trust-aware big data task scheduling approach in cloud computing environments.
Future Gener. Comput. Syst., 2020

Cloud federation formation using genetic and evolutionary game theoretical models.
Future Gener. Comput. Syst., 2020

A two-level solution to fight against dishonest opinions in recommendation-based trust systems.
CoRR, 2020

A Game-Theoretic Approach for Distributed Attack Mitigation in Intelligent Transportation Systems.
Proceedings of the NOMS 2020, 2020

A Trust and Energy-Aware Double Deep Reinforcement Learning Scheduling Strategy for Federated Learning on IoT Devices.
Proceedings of the Service-Oriented Computing - 18th International Conference, 2020

A Game-Based Secure Trading of Big Data and IoT Services: Blockchain as a Two-Sided Market.
Proceedings of the Service-Oriented Computing - 18th International Conference, 2020

Generative Adversarial Networks for Mitigating Biases in Machine Learning Systems.
Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

2019
MAPLE: A <i>M</i>achine <i>L</i>earning Approach for <i>E</i>fficient <i>P</i>lacement and <i>A</i>djustment of Virtual Network Functions.
J. Netw. Comput. Appl., 2019

On the Detection of Passive Malicious Providers in Cloud Federations.
IEEE Commun. Lett., 2019

IoTCocoa - an IoT platform to assist gourmet cocoa production.
Proceedings of the 2019 IEEE Latin-American Conference on Communications, 2019

Deep Smart Scheduling: A Deep Learning Approach for Automated Big Data Scheduling Over the Cloud.
Proceedings of the 7th International Conference on Future Internet of Things and Cloud, 2019

2018
Towards Trustworthy Multi-Cloud Services Communities: A Trust-Based Hedonic Coalitional Game.
IEEE Trans. Serv. Comput., 2018

2017
I Know You Are Watching Me: Stackelberg-Based Adaptive Intrusion Detection Strategy for Insider Attacks in the Cloud.
Proceedings of the 2017 IEEE International Conference on Web Services, 2017

On the Effects of User Ratings on the Profitability of Cloud Services.
Proceedings of the 2017 IEEE International Conference on Web Services, 2017

2016
CEAP: SVM-based intelligent detection model for clustered vehicular ad hoc networks.
Expert Syst. Appl., 2016

A Stackelberg game for distributed formation of business-driven services communities.
Expert Syst. Appl., 2016

How to Distribute the Detection Load among Virtual Machines to Maximize the Detection of Distributed Attacks in the Cloud?
Proceedings of the IEEE International Conference on Services Computing, 2016

2015
A survey on trust and reputation models for Web services: Single, composite, and communities.
Decis. Support Syst., 2015

A Cooperative Detection Model Based on Artificial Neural Network for VANET QoS-OLSR Protocol.
Proceedings of the IEEE International Conference on Ubiquitous Wireless Broadband, 2015

Misbehavior Detection Framework for Community-Based Cloud Computing.
Proceedings of the 3rd International Conference on Future Internet of Things and Cloud, 2015

2014
A Dempster-Shafer Based Tit-for-Tat Strategy to Regulate the Cooperation in VANET Using QoS-OLSR Protocol.
Wirel. Pers. Commun., 2014

A cooperative watchdog model based on Dempster-Shafer for detecting misbehaving vehicles.
Comput. Commun., 2014

<i>DARM</i>: a privacy-preserving approach for distributed association rules mining on horizontally-partitioned data.
Proceedings of the 18th International Database Engineering & Applications Symposium, 2014

2013
VANET QoS-OLSR: QoS-based clustering protocol for Vehicular Ad hoc Networks.
Comput. Commun., 2013


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