Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Moudoud, H.; Houda, Z. A. El; Brik, B.
Securing O-RAN with Zero Trust Architecture and Large Language Models Proceedings Article
In: C., Iwendi; Z., Boulouard; N., Kryvinska (Ed.): Lect. Notes Networks Syst., pp. 357–368, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 23673370 (ISSN); 978-303194619-6 (ISBN), (Journal Abbreviation: Lect. Notes Networks Syst.).
Abstract | Links | BibTeX | Tags: Access management, Access Management system, Architecture, Authentication, Block-chain, Blockchain, Computer architecture, Computer crime, Cryptography, Distributed computer systems, Intrusion Detection, Language model, Large language model, Management systems, Mobile security, Mobile telecommunication systems, Network architecture, Network security, O-RAN, Open radio access network, Radio access networks, Security systems, Security vulnerabilities, Trusted computing, Zero Trust
@inproceedings{moudoudSecuringORANZero2025,
title = {Securing O-RAN with Zero Trust Architecture and Large Language Models},
author = {H. Moudoud and Z. A. El Houda and B. Brik},
editor = {Iwendi C. and Boulouard Z. and Kryvinska N.},
url = {https://www.scopus.com/pages/publications/105011259647?origin=resultslist},
doi = {10.1007/978-3-031-94620-2_31},
isbn = {23673370 (ISSN); 978-303194619-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Networks Syst.},
volume = {1312 LNNS},
pages = {357–368},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The Open Radio Access Network (O-RAN) architecture is critical for the development of 6G networks, offering flexibility and interoperability through disaggregated components. However, this openness exposes O-RAN to new security vulnerabilities, including unauthorized access, data breaches, and malicious xApp deployments. To address these challenges, we propose DistillORAN, a novel Zero-Trust architecture designed specifically for O-RAN. DistillORAN features two core components: (1) a blockchain-based decentralized trust management system for secure verification, authentication, and dynamic access control of xApps, and (2) a lightweight intrusion detection module powered by DistilBERT, a transformer-based model optimized for resource-constrained environments. DistilBERT’s ability to analyze network activities and detect anomalies in real-time allows it to identify complex security threats and multi-step attack scenarios within the O-RAN ecosystem. Its lightweight nature makes it ideal for O-RAN’s distributed infrastructure, where computational resources may be limited. By combining blockchain technology for trust management with DistilBERT’s powerful pattern recognition for intrusion detection, DistillORAN enforces a Zero-Trust security model, ensuring continuous monitoring and verification of all network components. This comprehensive solution enhances the security and resilience of O-RAN networks, aligning with the dynamic needs of next-generation mobile infrastructures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
note = {Journal Abbreviation: Lect. Notes Networks Syst.},
keywords = {Access management, Access Management system, Architecture, Authentication, Block-chain, Blockchain, Computer architecture, Computer crime, Cryptography, Distributed computer systems, Intrusion Detection, Language model, Large language model, Management systems, Mobile security, Mobile telecommunication systems, Network architecture, Network security, O-RAN, Open radio access network, Radio access networks, Security systems, Security vulnerabilities, Trusted computing, Zero Trust},
pubstate = {published},
tppubtype = {inproceedings}
}
The Open Radio Access Network (O-RAN) architecture is critical for the development of 6G networks, offering flexibility and interoperability through disaggregated components. However, this openness exposes O-RAN to new security vulnerabilities, including unauthorized access, data breaches, and malicious xApp deployments. To address these challenges, we propose DistillORAN, a novel Zero-Trust architecture designed specifically for O-RAN. DistillORAN features two core components: (1) a blockchain-based decentralized trust management system for secure verification, authentication, and dynamic access control of xApps, and (2) a lightweight intrusion detection module powered by DistilBERT, a transformer-based model optimized for resource-constrained environments. DistilBERT’s ability to analyze network activities and detect anomalies in real-time allows it to identify complex security threats and multi-step attack scenarios within the O-RAN ecosystem. Its lightweight nature makes it ideal for O-RAN’s distributed infrastructure, where computational resources may be limited. By combining blockchain technology for trust management with DistilBERT’s powerful pattern recognition for intrusion detection, DistillORAN enforces a Zero-Trust security model, ensuring continuous monitoring and verification of all network components. This comprehensive solution enhances the security and resilience of O-RAN networks, aligning with the dynamic needs of next-generation mobile infrastructures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
2.
Davoust, A.; Gavigan, P.; Ruiz-Martin, C.; Trabes, G.; Esfandiari, B.; Wainer, G.; James, J.
An architecture for integrating BDI agents with a simulation environment Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12058 LNAI, pp. 67–84, 2020, ISSN: 03029743, (ISBN: 9783030514167).
Abstract | Links | BibTeX | Tags: Antennas, Architecture, Autonomous agents, Belief-desire-intentions, Impedance mismatch, Modelling and simulations, Multi agent systems, Open source architecture, Real time simulations, Separation of concerns, Simulated environment, Simulation environment
@article{davoust_architecture_2020,
title = {An architecture for integrating BDI agents with a simulation environment},
author = {A. Davoust and P. Gavigan and C. Ruiz-Martin and G. Trabes and B. Esfandiari and G. Wainer and J. James},
editor = {Lesperance Y. Bordini R.H. Dennis L.A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088750329&doi=10.1007%2f978-3-030-51417-4_4&partnerID=40&md5=2f742500bcd9cac1bf054bbc8802e39c},
doi = {10.1007/978-3-030-51417-4_4},
issn = {03029743},
year = {2020},
date = {2020-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {12058 LNAI},
pages = {67–84},
publisher = {Springer},
abstract = {We present Simulated Autonomous Vehicle Infrastructure (SAVI), an open source architecture for integrating Belief-Desire-Intention (BDI) agents with a simulation platform. This allows for separation of concerns between the development of complex multi-agent behaviours and simulated environments to test them in. We identify and address the impedance mismatch between modelling and simulation, where time is explicitly modelled and differs from “wall clock” time, and BDI systems, where time is not explicitly managed. Our approach avoids linking the environment’s simulation time step to the agents’ reasoning cycles, relying instead on real time simulation where possible, and ensuring that the reasoning module does not get ahead of the simulation. This contributes to a realistic approximation of a real environment for the simulated BDI agents. This is accomplished by running the simulation cycles and the agent reasoning cycles each in their own threads of execution, and managing a single point of contact between these threads. Finally, we illustrate the use of our architecture with a case study involving the simulation of Unmanned Aerial Vehicles (UAVs) following birds. © Springer Nature Switzerland AG 2020.},
note = {ISBN: 9783030514167},
keywords = {Antennas, Architecture, Autonomous agents, Belief-desire-intentions, Impedance mismatch, Modelling and simulations, Multi agent systems, Open source architecture, Real time simulations, Separation of concerns, Simulated environment, Simulation environment},
pubstate = {published},
tppubtype = {article}
}
We present Simulated Autonomous Vehicle Infrastructure (SAVI), an open source architecture for integrating Belief-Desire-Intention (BDI) agents with a simulation platform. This allows for separation of concerns between the development of complex multi-agent behaviours and simulated environments to test them in. We identify and address the impedance mismatch between modelling and simulation, where time is explicitly modelled and differs from “wall clock” time, and BDI systems, where time is not explicitly managed. Our approach avoids linking the environment’s simulation time step to the agents’ reasoning cycles, relying instead on real time simulation where possible, and ensuring that the reasoning module does not get ahead of the simulation. This contributes to a realistic approximation of a real environment for the simulated BDI agents. This is accomplished by running the simulation cycles and the agent reasoning cycles each in their own threads of execution, and managing a single point of contact between these threads. Finally, we illustrate the use of our architecture with a case study involving the simulation of Unmanned Aerial Vehicles (UAVs) following birds. © Springer Nature Switzerland AG 2020.