Assoc. Prof. Madhusanka Liyanage

Associate Professor / Ad Astra Fellow and Director of Graduate Research, School of Computer Science, University College Dublin, Ireland

Madhusanka Liyanage is an Assistant Professor/Ad Astra Fellow and Director of Graduate Research at 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 Jarawardhenepura, Sri Lanka. He holds a Doctor of Technology degree from the University of Oulu, Finland (2016) and prestigious fellowships during 2018-2020. Madhusanka has been a Visiting Research Fellow at various renowned institutions globally. He received the "2020 IEEE ComSoc Outstanding Young Researcher" award and was ranked among the World's Top 2% of Scientists in 2021 and 2022. He has over 150+ publications, authored books, edited books, and two patents. Additionally, he serves as an expert consultant at European Union Agency for Cybersecurity (ENISA) and has secured over 5 Million Euro research funding. Currently, he leads three large EU H2020/Horizon Europe projects and is the director of the Netslab team at University College Dublin, Ireland. More info: www.madhusanka.com 

Dr Vera Stavroulaki

Vera Stavroulaki is a technology developer and Co-founder of WINGS ICT Solutions (https://www.wings-ict-solutions.eu/). She is the Managing Director of diTTo BV (https://ditto-engineering.com/). She has 20 years of experience, working on the design and development of intelligent cloud-based IoT applications and data platforms in various vertical domains and Digital Twin solutions. She has actively participated in EU funded research projects of the FP7/ICT, FP6/IST and FP5/IST frameworks and is currently involved in various H2020 projects. She is the Project coordinator of the H2020 DEDICAT and the JU SNS CONFIDENTIAL6G projects. She has served as a co-coordinator of the IERC AC3 “IoT innovation and pilots” and as a Rapporteur of the Technical Report ETSI TR 102 684 “Reconfigurable Radio Systems (RRS); Feasibility Study on Control Channels for Cognitive Radio Systems”. She has authored more than 100 publications in international journals and refereed conferences.

 Dr Luis Muñoz-González 

Dr Luis Muñoz-González is a senior research scientist at Telefónica Research in Barcelona, Spain. Before that, he worked as a research associate in the Department of Computing at Imperial College London, being part of the Resilient Information Systems Security (RISS) group. Dr Muñoz-González obtained a PhD on machine learning at University Carlos III of Madrid, Spain. His PhD thesis on Gaussian Process models for nonstationary regression was recognized with the Extraordinary Doctorate Award. His current research interests lie at the intersection of machine learning and cyber security, including the security of machine learning, federated learning, and machine learning for cyber security.

Abstract: At training time, Federated Learning algorithms can be vulnerable to data and model poisoning attacks, where attackers can manipulate the parameters of the global model to produce indiscriminate or targeted errors when the model is deployed. In this talk we present, adaptive federated averaging, a technique for mitigating the effect of such attacks and detect the malicious participants trying to compromise a federated learning task, including a robust aggregation algorithm capable of ignoring malicious updates and a Hidden Markov Model to model the participants’ behaviour during training.

Assoc. Prof. Sandra Scott-Hayward (Queen's University Belfast)

Sandra Scott-Hayward is an Associate Professor with the School of Electronics, Electrical Engineering and Computer Science, and a Member of the Centre for Secure Information Technologies at Queen’s University Belfast (QUB). She began her career in industry and became a Chartered Engineer in 2006. Since joining academia, she has contributed security designs and solutions for softwarized networks based on her research on network security architectures and security functions for emerging networks, specifically considering threat detection and protection mechanisms in programmable networks. She received Outstanding Technical Contributor and Outstanding Leadership awards from the Open Networking Foundation in 2015 and 2016, respectively, having been elected and serving as the Vice-Chair of the ONF Security Working Group from 2015 to 2017. Dr. Scott-Hayward serves on the editorial board for IEEE Transactions on Network and Service Management, and IEEE Transactions on Machine Learning in Communications and Networking. She is Vice-Chair of the IEEE NetSoft Steering Committee. She is Director of the QUB Academic Centre of Excellence in Cyber Security Education (ACE-CSE), co-lead of the QUB Leverhulme Interdisciplinary Network on Algorithmic Solutions (LINAS) doctoral training programme, and a Polymath Fellow of the Global Fellowship Initiative at the Geneva Centre for Security Policy (GCSP) from 2021 to 2023. With LINAS and GCSP, she explores the impact of ML and AI technologies on security and society.

Abstract: Space-air-ground integrated networks (SAGINs) extend terrestrial network infrastructure to non-ter­restrial networks (NTNs), integrating satellite and unmanned aerial vehicle communications, high-altitude platforms, and space systems. These integrated networks can provide connectivity to remote locations, enhance service delivery, and support new ventures. NTN integration is an ambitious mission in 3GPP to extend the Internet to sky and outer space. Machine learning (ML) and artificial intelli­gence (AI) solutions are being explored to advance cooperative and autonomous behaviour, self-organisation, and optimisation in SAGINs with associated security challenges. In this talk, we will explore the security, intelligence, and programmable aspects of SAGIN.

Konstantinos Lessis & Christina Karousatou

Dr Christina Karousatou is a solution architect in WINGS ICT Solutions. She received her PhD in Computer Science from Aix-Marseille University in 2017 and continued her research on mathematical optimization problems at TU Darmstadt as a post-doctoral fellow till 2020. In 2022 she joined the WINGS ICT solutions team and has undertaken task leading and work package leading roles in various EU funded research projects.

Konstantinos Lessis is a data scientist at WINGS ICT Solutions. He has participated in several research and development projects. His research interests focus on the design, and development of Machine Learning models, with an emphasis on the use of ML and AI in cybersecurity, anomaly detection in critical-infrastructures, predictive maintenance and supply chain optimization.

Abstract: Federated learning provides a new way to use Machine Learning models as there is no need to exchange data. The only information exchange between the nodes regards the ML model’s parameters like the weights of a deep neural network. Although FL makes it possible to extract knowledge of training data without direct data exchange, transmitting the model updates could enable an attacker to infer private data. Our proposal for secure FL leverages the (Fully) Homomorphic Encryption (FHE) approach. FHE enables computation on encrypted data without the need for decryption, thus offering a robust solution for privacy-preserving FL. In this presentation we will examine the design considerations for integrating FHE into the Federated Learning model built for CONFIDENTIAL 6G use cases.

Shush Liu (Nokia)

Shushu Liu is currently a researcher at Nokia Bell Labs, Espoo, Finland. She received the Ph.D. degree from Department of Communication and Networking, Aalto University, Espoo, Finland, in 2022. Her research interests are in security and privacy in 5G/6G network. Dr. Liu is author of more than 20 peer-reviewed publications and is serving as reviewer of Wireless Communication Magazine, IEEE Internet of Things Journal, IEEE Access Journal, Information Sciences, etc.
Abstract: The sixth generation (6G) of cellular networks is expected to provide a reliable, trustworthy, and resilient service with substantial increase of coverage and network heterogeneity. The emerging technologies such as post-quantum cryptography (PQC), artificial intelligence (AI), machine learning (ML) and distributed ledger technology (DLT) are playing a significant role in achieving the 6G objectives. This talk focuses on confidential networking in 6G, referring to the protection of data transmitted over networks with encryption and secure protocols such as Transport Layer Security (TLS) with regards to new requirements and architectures for the 6G security and privacy such as authentication, encryption, access control and communication. 

Engin Zydan (CTTC)

Engin Zeydan received his PhD degree in February 2011 from the Department of Electrical and Computer Engineering at Stevens Institute of Technology, Hoboken, NJ, USA. He is currently a senior researcher in the Services as Networks (SaS) Research Unit in CTTC in Barcelona, Spain. He was the Project Coordinator of the European H2020 5GPP MonB5G project (2021-2023). Dr. Engin Zeydan has many years of experience as a researcher in EU Framework Programmes at technical and administrative levels in both industry and research organizations and has been involved in several projects including FP7 STREPs, Celtic, ITEA and H2020 as Technical Lead and WP Lead. His research activities include outstanding publications (more than 120 papers in leading conferences and journals and 10 national patents) and successful participation in research-funded projects mainly focused on telecommunications and data science/engineering.

Abstract: This talk will focus on the latest advances in security and trust mechanisms related to network orchestration and management. As networks become more complex and extensive, ensuring robust security and maintaining trust are of paramount importance. We will discuss innovative strategies and technologies that are shaping the future of network security, including the integration of AI-driven solutions, blockchain technology for greater transparency and trust. The talk will also provide insight into how these recent advances can effectively mitigate risks in network management and ensure reliable network operations in an increasingly connected world.

Dr Julian Thomas (Friedrich-Alexander-Universität)

Julian Thomas is a PhD student in cryptography at the Friedrich-Alexander-Universität Erlangen-Nürnberg in Germany, and He is working on the European Confidential 6G project. His research interested are in the formalizations and automatication of privacy-enhancing cryptographic primitives as well as post-quantum cryptography.

Abstract: Message authentication codes are a fundamental symmetric key primitive to ensure authenticity and integrity. We present the first framework to comprehensively and automatically generate and analyze secure deterministic message authentication codes based on pseudorandom functions.

Assoc. Prof. Madhusanka Liyanage

Madhusanka Liyanage is an Associate Professor/Ad Astra Fellow and Director of Graduate Research at 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 Jarawardhenepura, Sri Lanka. He holds a Doctor of Technology degree from the University of Oulu, Finland (2016) and prestigious fellowships from 2018 to 2020. Madhusanka has been a Visiting Research Fellow at various renowned institutions globally. He received the "2020 IEEE ComSoc Outstanding Young Researcher" award and was ranked among the World's Top 2% of Scientists in 2021, 2022, and 2023. He has over 200+ publications, authored books, edited books, and two patents. Additionally, he serves as an expert consultant at the European Union Agency for Cybersecurity (ENISA) and has secured over 5 Million euros in research funding. Currently, he leads three large EU H2020/Horizon Europe projects and is the director of the Netslab team at University College Dublin, Ireland. More info: www.madhusanka.com

Abstract: The exponential growth in connected devices with Internet-of-Things (IoT) and next-generation wireless networks requires more advanced and dynamic spectrum access mechanisms. Blockchain-based approaches to Dynamic Spectrum Access (DSA) seem efficient and robust due to their inherited characteristics such as decentralization, immutability and transparency. However, conventional consensus mechanisms used in blockchain networks are expensive to be used due to the cost, processing and energy constraints. Moreover, none of the blockchain-based DSA systems can efficiently address spectrum violation (i.e., unauthorized access to the spectrum). To address these issues, we propose a newly tailored energy-efficient consensus mechanism called Distributed-Proof-of-Sense (DPoS) that is specially designed to enable DSA and detect spectrum violations. The proposed consensus algorithm motivates blockchain miners to perform spectrum sensing, which leads to the collection of a full spectrum of sensing data. An elliptic curve cryptography-based zero-knowledge proof is used as the core of the proposed mechanism. With the potential of blockchain and smart contracts, the proposed DSA system can provide service automation and real-time spectrum marketplace features as well.

Drasko Draskovi

Drasko is an IoT expert with over 15 years of professional experience. He hacked embedded Linux SW and HW device drivers, designing complex wireless systems in telecom industry: he was working on OMAP platform in Texas Instruments, designed 4G multi-protocol femto-cells in Alcatel-Lucent and worked on 5G and blockchain solutions in Nokia. Drasko earned his reputation in open-source community as an author of numerous projects - like WeIO or Mainflux. He is one of the main contributors of the Linux Foundation's EdgeX Foundry project. Drasko is an author of the book "Scalable Architecture for the Internet of Things" published by O'Reilly and vivid conference speaker, sharing his thoughts on modern software design and how Internet should be decentralized. He holds a MSc in Electrical Engineering from Belgrade University.