TUTORIALS
1. Engineering the Security and Privacy of Open RAN: Principles, Tools, and Practices
Liyanage Madhusanka (1), Engin Zeydan (2), Abdullah Aydeger (3)
(1) Associate Professor, School of Computer Science, University College Dublin, Ireland
(2) Senior Researcher, Centre Tecnologic de Telecomunicacions de Catalunya (CTTC), Spain
(3) Assistant Professor, Department of Electrical Engineering and Computer Science, Florida Institute of Technology (FIT), United States of America
June 24, 14:00-18:00, Da Vinci Room
Abstract
Open RAN (O-RAN) is an emerging industry framework for Radio Access Networks that introduces open, standardized interfaces to enable interoperability among equipment from multiple vendors, improving flexibility and reducing costs. It leverages advances in network softwarization and Artificial Intelligence to optimize the performance and management of RAN components. By promoting an open ecosystem, O-RAN creates opportunities for a wide range of stakeholders to contribute to and build customized RAN solutions. Despite these advantages, the shift to O-RAN also introduces new security and privacy concerns. Its architecture differs significantly from traditional RAN deployments, and without proper safeguards, this openness could expose networks to substantial risks. This tutorial presents an in-depth examination of the security and privacy challenges associated with O-RAN architecture, along with mitigation strategies and ongoing standardization efforts. It further explores how O-RAN can support advanced protection mechanisms for 5G and beyond, complemented by practical insights and demonstrations.
Dr. Madhusanka Liyanage is an Associate Professor/Ad Astra Fellow and Director of Network Softwarization and Security Labs (NetsLab) at the School of Computer Science, University College Dublin, Ireland. He is also a Docent/Adjunct Professor at the University of Oulu, Finland, the University of Ruhuna, Sri Lanka and the University of Sri Jayawardhanapura, Sri Lanka. He received his Doctor of Technology degree in communication engineering from the University of Oulu, Oulu, Finland, in 2016. He also received the prestigious Marie Skłodowska-Curie Actions Individual Fellowship and the Government of Ireland Postdoctoral Fellowship during 2018-2020. He was a Visiting Research Fellow at the CSIRO, Australia, the Infolabs21, Lancaster University, U.K.; Computer Science and Engineering, The University of New South Wales, Australia; School of I.T., University of Sydney, Australia, LIP6, Sorbonne University, France and Computer Science and Engineering, The University of Oxford, U.K. He is also a senior member of IEEE. In 2020, he received the ”2020 IEEE ComSoc Outstanding Young Researcher” award by IEEE ComSoc EMEA. In 2021, 2022 and 2023, he was ranked among the world’s top 2% of scientists (2020, 2021, 2022 & 2023) on the list prepared by Elsevier BV, Stanford University, USA. Also, he was awarded an Irish Research Council (IRC) Research Ally Prize as part of the IRC Researcher of the Year 2021 and 2023 awards for his positive impact as a supervisor. In 2022, he received ”the 2022 Tom Brazil Excellence in Research Award” from the SFI CONNECT Center. Moreover, Madhusanka received a special commendation from the Irish Research Council Ireland for being the IRC Early Career Researcher of 2022. He has co-authored over 250 publications, including three authored books, four edited books with Wiley, and two patents (Google Citations: 19000+, h-index: 60+). Moreover, He has received four Best Paper Awards for SDMN security (at NGMAST 2015), 5G Security (at IEEE CSCN 2017), MEC Security (IEEE MCE 2021) and 5G IoT (ICT Express 2022). Additionally, he has been awarded two research grants and 19 other prestigious awards/scholarships during his research career. Liyanage has worked for more than fifteen E.U., international and national projects in the ICT domain. Moreover, he was the Finnish national coordinator for EU COST Action CA15127 on resilient communication services. He serves as a management committee member for three other EU COST action projects: EU COST Action IC1301, IC1303, CA15107, CA16226, CA2011, and CA20136. Liyanage has over six years of experience in research project management, research group leadership, proposal preparation, project progress documentation, and graduate student co-supervision/mentoring. He has secured over 10 Million euros in research funding via various research projects. He is a P.I. for three large EU H2020/Horizon Europe projects. As a leader of work packages in several projects, he held responsibilities, including SIGMONA and Naked approach projects. Additionally, two research projects (MEVICO and SIGMONA projects) received the CELTIC Excellence and CELTIC Innovation Awards in 2013, 2017, and 2018. He is also an expert consultant at the European Union Agency for Cybersecurity (ENISA). In 2021, Liyanage was elevated as a Funded Investigator of the Science Foundation Ireland CONNECT Research Centre, Ireland. Moreover, he is an expert reviewer at different funding agencies in France, Qatar, UAE, Sri Lanka, and Kazakhstan.
Dr. Engin Zeydan is a Senior Researcher in the Services as networks (SaS) at Centre Tecnologic de Telecomunicacions de Catalunya (CTTC) in Barcelona, Spain. He received his PhD degree from the Department of Electrical and Computer Engineering at Stevens Institute of Technology, Hobo- ken, NJ, USA in 2011 and M.S. and B.S. degrees from the Department of Electrical and Electronics Engineering at Middle East Technical University, Ankara, Turkey, in 2006 and 2004, respectively. Before joining CTTC in 2018, he worked as an R&D Engineer for Avea (a Turkish mobile operator) between 2011 and 2016, as Senior R&D Engineer in Turk Telekomunikasyon A.S between 2016 and 2018 and a part-time instruction at Electrical and Electronics Engineering department of Ozyegin University between January 2015 and June 2018. Dr. Zeydan has been primarily responsible for carrying out European Commission and nationally funded research activities at CTTC, T¨ urk Telekomunikasyon, Avea. He is currently the Project Coordinator of the Horizon Eu- rope UNITY-6G European Project (January 2025-December 2027). He was the Project Coordinator of the Horizon 2020 MonB5G European Project (November 2021-April 2023). He has also been involved in other European level projects such as H2020 projects 5Growth (2019-2022) and Clear5G (as WP leader, 2017-2018), FP7 projects MOTO (as WP leader, 2012-2015) and CROWD (2014-2015) in collaborations with various industries and universities. He is co-author of over 150+ papers in international journals and conferences and 12 patents (11 granted in Turkish Patent Institute and 1 granted under European Patent Office). His research interests are in the areas of telecommunications, data engineering/science and network security.
Dr. Abdullah Aydeger is currently an assistant professor at the Electrical Engineering and Computer Science Department at FIT. Prior to joining FIT in August 2022, he was an assistant professor at the School of Computing at Southern Illinois University, Carbondale, since 2020. Dr. Aydeger obtained a Ph.D. Degree in Computer and Electrical Engineering from Florida International University in 2020. His research interests are post-quantum cryptography, network security, and virtualization.
2. Network-Aware Distributed Learning for Smart Mobility: Federated, Peer-to-Peer and Beyond
Joannes Sam Mertens J
Assistant Professor, DIEEI, University of Catania, Italy
June 25, 14:00-18:00, Da Vinci Room
Abstract
The rapid evolution of intelligent transportation systems is driving a paradigm shift toward data-driven, cooperative and autonomous mobility where vehicles and infrastructure continuously learn from distributed data sources. In this context, distributed machine learning has emerged as a key enabler for smart and safe mobility, allowing learning to take place directly within vehicular networks while addressing stringent constraints on latency, bandwidth, scalability and privacy. This tutorial provides a comprehensive overview of efficient distributed learning paradigms tailored to vehicular environments, with a particular focus on communication-aware and context-aware learning protocols. Specifically, it introduces state-of-the-art approaches for both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) learning scenarios. In V2V settings, the tutorial focuses on peer-to-peer learning mechanisms that allow vehicles to collaboratively exchange model updates in a fully decentralized manner. In V2I settings, it covers federated learning architectures in which vehicles act as edge learners and infrastructure nodes coordinate model aggregation while preserving data locality and privacy. The tutorial discusses how communication efficiency can be improved through selective and partial model exchange, such as layer-wise sharing strategies and neural network partitioning that separates vehicles specific user behaviour from road- and environment-specific patterns. The tutorial further explores how wireless channel conditions, model similarity among neighbouring nodes and network dynamics can be jointly exploited to enable adaptive peer-to-peer learning strategies for model dissemination.
Practical applications are illustrated through representative vehicular models, including CNN autoencoders for driving behaviour anomaly detection and safety-critical use cases. Overall, the tutorial equips researchers and students with the insights needed to design scalable, efficient and reliable distributed learning solutions for next-generation intelligent transportation systems and connected mobility scenarios.
Dr. Joannes Sam Mertens is an Assistant Professor with the Department of Electrical, Electronic and Computer Engineering at the University of Catania. He received his Bachelor’s and Master’s degrees in Electronics and Communication Engineering from SSN College of Engineering and earned his Ph.D. in 2022 from the University of Catania. His research focuses on distributed and collaborative machine learning for intelligent and infrastructureless networks, with applications in vehicular communications and smart mobility. He has contributed to European and several regional research projects, including SAMOTHRACE, COG-LO, SAFE-DEMON, Cycleshield, and DELIAS. Within the SAMOTHRACE project’s smart mobility pillar, he has been developing collaborative learning protocols for vehicular networks for the past three years. He has also delivered invited talks and keynote lectures on distributed AI for vehicular networks and healthcare applications.