Bouziane Brik

Orcid: 0000-0002-3267-5702

According to our database1, Bouziane Brik authored at least 81 papers between 2012 and 2025.

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

Timeline

Legend:

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Bibliography

2025
A privacy-preserving Self-Supervised Learning-based intrusion detection system for 5G-V2X networks.
Ad Hoc Networks, 2025

2024
Cooperative parking search strategy through V2X communications: an agent-based decision.
Wirel. Networks, November, 2024

Federated Deep Reinforcement Learning for Efficient Jamming Attack Mitigation in O-RAN.
IEEE Trans. Veh. Technol., July, 2024

Blockchain-Enabled Federated Learning for Enhanced Collaborative Intrusion Detection in Vehicular Edge Computing.
IEEE Trans. Intell. Transp. Syst., July, 2024

A decentralized blockchain-based authentication scheme for cross-communication in IoT networks.
Clust. Comput., June, 2024

On Adjusting Data Throughput in IoT Networks: A Deep-Reinforcement-Learning-Based Game Approach.
IEEE Internet Things J., April, 2024

Early Network Intrusion Detection Enabled by Attention Mechanisms and RNNs.
IEEE Trans. Inf. Forensics Secur., 2024

Guest Editorial: Special Issue on Resource-Efficient Collaborative Deep Learning Over B5G/6G Networks.
IEEE Open J. Commun. Soc., 2024

Federated learning for 5G and beyond, a blessing and a curse- an experimental study on intrusion detection systems.
Comput. Secur., 2024

Securing IIoT applications in 6G and beyond using adaptive ensemble learning and zero-touch multi-resource provisioning.
Comput. Commun., 2024

Time-efficient detection of false position attack in 5G and beyond vehicular networks.
Comput. Networks, 2024

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions.
IEEE Access, 2024

On the Performance Evaluation of Mobility Model-Based GPSR Routing Protocol in Flying Ad hoc Networks.
Proceedings of the 6th International Conference on Pattern Analysis and Intelligent Systems, 2024

Leveraging LLMs to eXplain DRL Decisions for Transparent 6G Network Slicing.
Proceedings of the 10th IEEE International Conference on Network Softwarization, 2024

Reputation-Aware Scheduling for Secure Internet of Drones: A Federated Multi-Agent Deep Reinforcement Learning Approach.
Proceedings of the IEEE INFOCOM 2024, 2024

Integrating Blockchain Technology with PKI for Secure and Interoperable Communication in 5G and Beyond Vehicular Networks.
Proceedings of the 21st IEEE Consumer Communications & Networking Conference, 2024

2023
Next-power: Next-generation framework for secure and sustainable energy trading in the metaverse.
Ad Hoc Networks, October, 2023

A survey on data dissemination in internet of vehicles networks.
J. Locat. Based Serv., July, 2023

Toward Securing Federated Learning Against Poisoning Attacks in Zero Touch B5G Networks.
IEEE Trans. Netw. Serv. Manag., June, 2023

On-Demand Security Framework for 5GB Vehicular Networks.
IEEE Internet Things Mag., June, 2023

A MEC-Based Architecture to Secure IoT Applications using Federated Deep Learning.
IEEE Internet Things Mag., March, 2023

Guest Editorial: Multi-Access Networking for Extended Reality and Metaverse.
IEEE Internet Things Mag., March, 2023

5G Vehicle-to-Everything at the Cross-Borders: Security Challenges and Opportunities.
IEEE Internet Things Mag., March, 2023

Toward Optimal MEC-Based Collision Avoidance System for Cooperative Inland Vessels: A Federated Deep Learning Approach.
IEEE Trans. Intell. Transp. Syst., February, 2023

When Collaborative Federated Learning Meets Blockchain to Preserve Privacy in Healthcare.
IEEE Trans. Netw. Sci. Eng., 2023

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions.
CoRR, 2023

A Survey on Explainable AI for 6G O-RAN: Architecture, Use Cases, Challenges and Research Directions.
CoRR, 2023

XAI-Enabled Fine Granular Vertical Resources Autoscaler.
Proceedings of the 9th IEEE International Conference on Network Softwarization, 2023

Securing Federated Learning through Blockchain and Explainable AI for Robust Intrusion Detection in IoT Networks.
Proceedings of the IEEE INFOCOM 2023, 2023

CROP: Cluster-Based Routing Using Optimized Framework for IoT-Based Precision Agriculture.
Proceedings of the IEEE International Conference on Communications, 2023

Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks.
Proceedings of the IEEE International Conference on Communications, 2023

A Lightweight 5G-V2X Intra-Slice Intrusion Detection System Using Knowledge Distillation.
Proceedings of the IEEE International Conference on Communications, 2023

2022
Guest Editorial Introduction to the Special Section on AI-Powered Internet of Everything (IoE) Services in Next-Generation Wireless Networks.
IEEE Trans. Netw. Sci. Eng., 2022

When Federated Learning Meets Game Theory: A Cooperative Framework to Secure IIoT Applications on Edge Computing.
IEEE Trans. Ind. Informatics, 2022

GSS-VF: A Game-Theoretic Approach for Service Discovery in Fog Network of Vehicles.
IEEE Trans. Green Commun. Netw., 2022

Fog-supported Low-latency Monitoring of System Disruptions in Industry 4.0: A Federated Learning Approach.
ACM Trans. Cyber Phys. Syst., 2022

An end-to-end trusted architecture for network slicing in 5G and beyond networks.
Secur. Priv., 2022

"Why Should I Trust Your IDS?": An Explainable Deep Learning Framework for Intrusion Detection Systems in Internet of Things Networks.
IEEE Open J. Commun. Soc., 2022

Deep Learning for B5G Open Radio Access Network: Evolution, Survey, Case Studies, and Challenges.
IEEE Open J. Commun. Soc., 2022

A Novel IoT-Based Explainable Deep Learning Framework for Intrusion Detection Systems.
IEEE Internet Things Mag., 2022

NRflex: Enforcing network slicing in 5G New Radio.
Comput. Commun., 2022

Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach.
IEEE Access, 2022

Deep Learning-based Intra-slice Attack Detection for 5G-V2X Sliced Networks.
Proceedings of the 95th IEEE Vehicular Technology Conference, 2022

A Low-Latency Fog-based Framework to secure IoT Applications using Collaborative Federated Learning.
Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022

Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems.
Proceedings of the 47th IEEE Conference on Local Computer Networks, 2022

Federated Deep Learning-Based Framework to Avoid Collisions Between Inland Ships.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

Adaptive Resource Reservation to Survive Against Adversarial Resource Selection Jamming Attacks in 5G NR-V2X Distributed Mode 2.
Proceedings of the IEEE International Conference on Communications, 2022

Edge Computing-enabled Intrusion Detection for C-V2X Networks using Federated Learning.
Proceedings of the IEEE Global Communications Conference, 2022

A Trust and Explainable Federated Deep Learning Framework in Zero Touch B5G Networks.
Proceedings of the IEEE Global Communications Conference, 2022

DRIVE-B5G: A Flexible and Scalable Platform Testbed for B5G-V2X Networks.
Proceedings of the IEEE Global Communications Conference, 2022

2021
Toward Optimal MEC Resource Dimensioning for a Vehicle Collision Avoidance System: A Deep Learning Approach.
IEEE Netw., 2021

On using reinforcement learning for network slice admission control in 5G: Offline vs. online.
Int. J. Commun. Syst., 2021

Toward the Integration of UAVs' Services into the Cloud.
IEEE Commun. Stand. Mag., 2021

A renewable energy-aware power allocation for cloud data centers: A game theory approach.
Comput. Commun., 2021

A Trust architecture for the SLA management in 5G networks.
Proceedings of the ICC 2021, 2021

2020
On Link Stability Metric and Fuzzy Quantification for Service Selection in Mobile Vehicular Cloud.
IEEE Trans. Intell. Transp. Syst., 2020

An Edge-Based Social Distancing Detection Service to Mitigate COVID-19 Propagation.
IEEE Internet Things Mag., 2020

Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems.
IEEE Access, 2020

AutoMEC: LSTM-based User Mobility Prediction for Service Management in Distributed MEC Resources.
Proceedings of the MSWiM '20: 23rd International ACM Conference on Modeling, 2020

On Predicting Service-oriented Network Slices Performances in 5G: A Federated Learning Approach.
Proceedings of the 45th IEEE Conference on Local Computer Networks, 2020

Service-Oriented MEC Applications Placement in a Federated Edge Cloud Architecture.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019
Wireless communication in internet of vehicles networks: DSRC-based Vs cellular-based.
Proceedings of the 4th International Conference on Smart City Applications, 2019

ThermCont: A machine Learning enabled Thermal Comfort Control Tool in a real time.
Proceedings of the 15th International Wireless Communications & Mobile Computing Conference, 2019

Ranking Fog nodes for Tasks Scheduling in Fog-Cloud Environments: A Fuzzy Logic Approach.
Proceedings of the 15th International Wireless Communications & Mobile Computing Conference, 2019

Power Dispatching in Cloud Data Centers Using Smart Microgrids: A Game Theory Approach.
Proceedings of the 2019 IEEE Global Communications Conference, 2019

Accuracy and Localization-Aware Rescheduling for Flexible Flow Shops in Industry 4.0.
Proceedings of the 6th International Conference on Control, 2019

PUBLISH: A Distributed Service Advertising Scheme for Vehicular Cloud Networks.
Proceedings of the 16th IEEE Annual Consumer Communications & Networking Conference, 2019

Towards Predicting System Disruption in Industry 4.0: Machine Learning-Based Approach.
Proceedings of the 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) / The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40 2019) / Affiliated Workshops, April 29, 2019

2018
Renting Out Cloud Services in Mobile Vehicular Cloud.
IEEE Trans. Veh. Technol., 2018

A Game Based Power Allocation in Cloud Computing Data Centers.
Proceedings of the 14th International Conference on Wireless and Mobile Computing, 2018

ThingsGame: when sending data rate depends on the data usefulness in IoT networks.
Proceedings of the 14th International Wireless Communications & Mobile Computing Conference, 2018

Indoor Thermal Comfort Collection of People with Physical Disabilities.
Proceedings of the 2018 International Symposium on Networks, Computers and Communications, 2018

GSS-VC: A game-theoretic approach for service selection in vehicular cloud.
Proceedings of the 15th IEEE Annual Consumer Communications & Networking Conference, 2018

2017
Vehicular Cloud Service Provider Selection: A Flexible Approach.
Proceedings of the 2017 IEEE Global Communications Conference, 2017

2016
ECDGP: extended cluster-based data gathering protocol for vehicular networks.
Wirel. Commun. Mob. Comput., 2016

DDGP: Distributed Data Gathering Protocol for vehicular networks.
Veh. Commun., 2016

Finding the most adequate public bus in Vehicular Clouds.
Proceedings of the 2016 International Conference on Wireless Networks and Mobile Communications, 2016

2015
Finding a Public Bus to Rent out Services in Vehicular Clouds.
Proceedings of the IEEE 82nd Vehicular Technology Conference, 2015

RCS-VC: renting out and consuming services in vehicular clouds based on LTE-A.
Proceedings of the 2015 Global Information Infrastructure and Networking Symposium, 2015

2013
Token-based Clustered Data Gathering Protocol(TCDGP) in vehicular networks.
Proceedings of the 2013 9th International Wireless Communications and Mobile Computing Conference, 2013

2012
An efficient and robust clustered data gathering protocol (CDGP) for vehicular networks.
Proceedings of the second ACM international symposium on Design and analysis of intelligent vehicular networks and applications, 2012


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