Bouziane Brik

Bouziane Brik

Associate Professor, Bourgogne university, France.

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I received the Engineering degree (Ranked First) in computer science and the Magister degree from the university of Laghouat, Algeria, in 2010 and 2013, respectively, and the Ph.D. degree from the university of Laghouat, Algeria, and the university of La Rochelle, France, in 2017. I am currently working as associate professor at Bourgogne university and DRIVE laboratory, in France. Before joining Burgundy university, I was a post-doc at university of Troyes, CESI school, and Eurecom school. I have been working on 5G network slicing in the context of H2020 European projects on 5G including MonB5G and 5GDrones. My research interests also include machine/deep learning for wireless networks.

I am an active member in many conferences' organizing committees such as Globecom, WCNC, ICC, GIIS, EAI, EAI CICom, etc. I actively organize different special issues in prestigious journals as well as conference workshops. I also acted or still act as a Reviewer of many IFIP, ACM, and IEEE conferences (ICC, Globecom, WCNC, IWCMC, GIIS, LCN, etc.) and journals such as IEEE transactions and magazines.

Bio

Email
bouziane.brik@gmail.com
Skype
bfaouzi3@skype.com
Phone
+33751-52-03-31
Address
4 Allée de Neubrandenburg, 58000, Nevers, France.

Education

PhD in Computer Science , University of Laghouat (Algeria) & La Rochelle (France)
2013 - 2017
Topic: Data collection and aggregation in mobile networks.
MSc in Computer Science , University of Laghouat (Algeria)
2010 - 2013
Topic: Study of data collection protocols in vehicular networks.
Engineering Degree in Computer science , University of Laghouat (ranked first)
2005 - 2010
Subject: Developement of road traffic simulator in Java.

R&D Experiences

Associate professor (Maître de conférences) at University of Bourgogne and DRIVE laboratory, France
September, 2020 - Present
Research Topics: Machine/Deep learning for 5G networks and beyond (B5G/6G), security and privacy-aware network slicing for B5G vehicular networks, Explainable AI for Wireless networking.
Post doctoral Fellow at Eurecom school/research centre, Nice, France
October, 2019 - August, 2020
I was involved in three European projects: H2020 5GDrones!, H2020 MonB5G!, and InDiD.
PostDoctoral at LINEACT Laboratory of CESI School, France.
October, 2018 - September, 2019
I have worked on national LOCADYN Project.
Junior Postdoctoral at ERA Team, University of Technology of Troyes (UTT), France
October, 2019 - August, 2020
I have worked on B.A.C project.
Doctoral fellowships at L3i Laboratory, University of La Rochelle, France
September, 2016 - June, 2017
I have worked on service offering and consumption in vehicular cloud, as a part of my PhD thesis.
Visiting researcher at L3i Laboratory, University of La Rochelle, France
February, 2016
During one month, I have started to work on service offering and consumption in vehicular cloud, as a part of my PhD thesis.

Teaching

Artificiel Intelligence for Autonomous cars (5th year engineering, Master AESM) at University of Bourgogne, France
Teaching Language: English.
Lectures: Part1, Part2, Part3, Part4, Part5, Part6.
Tutorials (TD): TD1, TD2.
Laboratory works (TP): Lab1, Lab2, Lab3.
Datasets for TP: Dataset0, Dataset1, Dataset2, Dataset3, Dataset4.
Vehicular Network (5th year engineering, Master AESM) at University of Bourgogne, France
Teaching Language: English.
Laboratory works (TP): Lab1(Network Commands), Lab2 (Introduction to Packet Tracer), Lab3 (Packet Tracer), Lab4 (Packet Tracer).
Initiation to Python (2nd year engineering) at University of Bourgogne, France.
Teaching Language: French.
Lectures : Lesson1, Lesson2, Lesson3, Lesson4.
Laboratory works (TP): Lab1, Lab2, Lab3, Lab4.
Introduction to Python (3rd year engineering) at University of Bourgogne, France.
Teaching Language: French.
Lectures : Lesson1, Lesson2, Lesson3, Lesson4, Lesson5.
Laboratory works (TP): Lab1, Lab2, Lab3, Lab4, Lab5.
Python for Industry (4th year engineering) at University of Bourgogne, France.
Teaching Language: French.
Lectures : Lesson1, Lesson2, Lesson3, Lesson4, Lesson5.
Laboratory works (TP): Lab1, Lab2, Lab3, Lab4, Lab5.
Functional analysis, Algorithms and programming (1st year engineering) at University of Bourgogne, France.
Teaching Language: French.
Tutorials (TD) : TBD.
Network Softwarization (Master 1) at Eurecom school, Nice, France.
Teaching Language: English.
Internet fo Things Protocols (Master 1) at Eurecom school, Nice, France.
Teaching Language: English.
Connected Internet fo Things (4th year engineering) at University of Technology of Troyes (UTT), France.
Teaching Language: French.

Projects

5G-INSIGHT at DRIVE laboratory, France
April, 2021 - September, 2024.
Funded: ANR French Research Agency and FNR Luxembourg Research agency (https://5g-insight.eu/).
Grant: 631,8 K/euro.
My Role: Workpackage/Tasks Leader.
Project Objective(s): Building novel security mechanisms ranging from attack detection to attack mitigation leveraging novel tools and paradigms such as federated deep learning, Blockchains and Deception Security.
Project Keywords: 5G, V2X Communication, Orchestrated Security and Privacy-aware Slicing, Single and Multiple Sources Attack, Attack Learning and Detection, Automated Attack Mitigation.
5G-VIA at DRIVE laboratory, France
September, 2021 - August, 2023
Funded: ANER (ACCUEIL DE NOUVELLE ÉQUIPE DE RECHERCHE) French agency.
Grant: 50 K/euro.
My Role: Principal Coordinator.
Project Objective(s): Build the 5G open air interface (OAI) platform} at DRIVE lab.
Project Keywords: 5G, Autonomous Vehicle, Testbed, Open Air Platform (OAI), Artificial Intelligence.
H2020 5GDrones! at Eurecom school/research centre, Nice, France.
April 2019 - March, 2022
Funded: European Union.
Grant: 12 870 578,75 €.
My Role: Workpackage/Tasks leader.
Project Objective(s): Create, implement and test network slices for some drone use cases on the top of 5G infrastructure.
Project Keywords: 5G, UAV Trial (use cases), Network slicing (eMBB, uRLLC, and mMTC), KPI, Artificial Intelligence.
H2020 MonB5G at Eurecom school/research centre, Nice, France.
September 2019 - August, 2022
Funded: European Union.
Grant: 5572491,25 €.
My Role: Workpackage/Tasks leader.
Project Objective(s): Enable a distributed zero-touch management of 5G's network slicing leveraging deep and federated learning.
Project Keywords: B5G, Distributed Zero touch network & Service Management (ZSM), Network Slicing, Federated Deep Learning.
InDiD at Eurecom school/research centre, Nice, France.
Summer 2019 - 2023
Funded: Connecting Europe Facility (CEF).
Grant: 10 766 707 €.
My Role: Workpackage/Tasks leader.
Project Objective(s): Enable cooperative intelligent transportation systems (C-ITS) based on both 5G networks and network slicing.
Project Keywords: B5G, C-ITS (Cooperative Intelligent Transport Systems), 5G, Network Slicing.
LOCADYN at LINEACT Laboratory of CESI School, France.
August 2017 - July 2019
Funded: Normandy Region.
Grant: 385 k€.
My Role: Workpackage/Tasks leader.
Project Objective(s): Design of a system disruption model based on resource localizations in Industry 4.0, leveraging machine learning algorithms.
Project Keywords: Industry 4.0, System Disruption, Localization, Machine Learning, Tasks rescheduling.
B.A.C at ERA Team, University of Technology of Troyes (UTT), France.
September 2016 - August 2018
Funded: Ex-Région Champagne Ardenne.
Grant: 100 k€.
My Role: Workpackage/Tasks leader.
Project Objective(s): Automate the thermal comfort evaluation of disabled people through deployed sensor networks and leveraging machine learning..
Project Keywords: Indoor Thermal Comfort, Disabled people, Machine Learning.

Selected Publications

Guest Editorial:

B. Brik, K. Dev, Y. Xiao, G. Han and A. Ksentini, "Guest Editorial Introduction to the Special Section on AI-Powered Internet of Everything (IoE) Services in Next-Generation Wireless Networks," in IEEE Transactions on Network Science and Engineering, vol. 9, no. 5, pp. 2952-2954, 1 Sept.-Oct. 2022, doi: 10.1109/TNSE.2022.3195385.

International Journals:

1. Z. A. E. Houda, B. Brik and S.M. Senouci, A Novel IoT-Based Explainable Deep Learning Framework for Intrusion Detection Systems. Accepted in IEEE Internet of Things Magazine, 2022.
2. Z. A. E. Houda, B. Brik and L. Khoukhi, "“Why Should I Trust Your IDS?”: An Explainable Deep Learning Framework for Intrusion Detection Systems in Internet of Things Networks," in IEEE Open Journal of the Communications Society, vol. 3, pp. 1164-1176, 2022, doi: 10.1109/OJCOMS.2022.3188750.
3. Z. Abou El Houda, B. Brik, A. Ksentini, L. Khoukhi and M. Guizani, "When Federated Learning Meets Game Theory: A Cooperative Framework to secure IIoT Applications on Edge Computing," in IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2022.3170347.
4. B. Brik, K. Boutiba and A. Ksentini, "Deep Learning for B5G Open Radio Access Network: Evolution, Survey, Case Studies, and Challenges," in IEEE Open Journal of the Communications Society, vol. 3, pp. 228-250, 2022, doi: 10.1109/OJCOMS.2022.3146618.
5. Bouziane Brik, Mourad Messaadia, M’hammed Sahnoun, Belgacem Bettayeb, and Mohamed Amin Benatia. 2022. Fog-supported Low-latency Monitoring of System Disruptions in Industry 4.0: A Federated Learning Approach. ACM Trans. Cyber-Phys. Syst. 6, 2, Article 14 (April 2022), 23 pages. https://doi.org/10.1145/3477272
6. M. A. Benblidia, B. Brik, M. Esseghir and L. Merghem-Boulahia, "Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach," in IEEE Access, vol. 10, pp. 66213-66226, 2022, doi: 10.1109/ACCESS.2022.3184721.
7. W. Hammedi, B. Brik and S. M. Senouci, "Toward Optimal MEC-Based Collision Avoidance System for Cooperative Inland Vessels: A Federated Deep Learning Approach," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2022.3154158.
8. Karim Boutiba, Adlen Ksentini, Bouziane Brik, Yacine Challal, Amar Balla, NRflex: Enforcing network slicing in 5G New Radio, Computer Communications, Volume 181, 2022, Pages 284-292, ISSN 0140-3664, https://doi.org/10.1016/j.comcom.2021.09.034.
9. Mohammed Anis Benblidia, Bouziane Brik, Moez Esseghir, Leila Merghem-Boulahia, A renewable energy-aware power allocation for cloud data centers: A game theory approach, Computer Communications, Volume 179, 2021, Pages 102-111, ISSN 0140-3664, https://doi.org/10.1016/j.comcom.2021.08.001.
10. B. Brik and A. Ksentini, "Toward Optimal MEC Resource Dimensioning for a Vehicle Collision Avoidance System: A Deep Learning Approach," in IEEE Network, vol. 35, no. 3, pp. 74-80, May/June 2021, doi: 10.1109/MNET.011.2000577.
11. Bouziane Brik, Moez Esseghir, Leila Merghem-Boulahia, Hichem Snoussi, An IoT-based deep learning approach to analyse indoor thermal comfort of disabled people, Building and Environment, Volume 203, 2021, 108056, ISSN 0360-1323, https://doi.org/10.1016/j.buildenv.2021.108056.
12. Bouziane Brik, Adlen Ksentini, Maha Bouaziz: Federated Learning for UAVs-Enabled Wireless Networks: Use Cases, Challenges, and Open Problems. IEEE Access 8: 53841-53849 (2020).

International Conferences:

1. S. Ben Saad, B. Brik, A. Ksentini. A Trust and Explainable Federated Deep Learning Framework in Zero Touch B5G Networks. Accepted in GLOBECOM 2022 - IEEE Global Communications Conference.
2. Z. A. El Houda, B. Brik and L. Khoukhi, "Ensemble Learning for Intrusion Detection in SDN-Based Zero Touch Smart Grid Systems," 2022 IEEE 47th Conference on Local Computer Networks (LCN), 2022, pp. 149-156, doi: 10.1109/LCN53696.2022.9843645.
3. W. Hammedi, B. Brik and S. M. Senouci, "Federated Deep Learning-Based Framework to Avoid Collisions Between Inland Ships," 2022 International Wireless Communications and Mobile Computing (IWCMC), 2022, pp. 967-972, doi: 10.1109/IWCMC55113.2022.9825393.
4. S. B. Saad, A. Ksentini and B. Brik, "A Trust architecture for the SLA management in 5G networks," ICC 2021 - IEEE International Conference on Communications, 2021, pp. 1-6, doi: 10.1109/ICC42927.2021.9500990.
5. B. Brik, P. A. Frangoudis and A. Ksentini, "Service-Oriented MEC Applications Placement in a Federated Edge Cloud Architecture," ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2020, pp. 1-6, doi: 10.1109/ICC40277.2020.9148814.
6. B. Brik and A. Ksentini, "On Predicting Service-oriented Network Slices Performances in 5G: A Federated Learning Approach," 2020 IEEE 45th Conference on Local Computer Networks (LCN), 2020, pp. 164-171, doi: 10.1109/LCN48667.2020.9314849.
7. Umberto Fattore, Marco Liebsch, Bouziane Brik, Adlen Ksentini: AutoMEC: LSTM-based User Mobility Prediction for Service Management in Distributed MEC Resources. MSWiM 2020: 155-159.
8. M. A. Benblidia, B. Brik, L. Merghem-Boulahia and M. Esseghir, "Ranking Fog nodes for Tasks Scheduling in Fog-Cloud Environments: A Fuzzy Logic Approach," 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), Tangier, Morocco, 2019, pp. 1451-1457. doi: 10.1109/IWCMC.2019.8766437

Platform

TBD

Contact

+33-751-52-03-31
bouziane.brik@gmail.com
bouziane.brik@u-bourgogne.fr