CSNet 2024 Keynotes 

Keynote #1

Title: AI-native 6G networks: security needs

Abstract: What does it mean that 6G networks will be AI-native? How to secure future networks? Could AI be a valuable asset for cybersecurity? Is an AI-driven cybersecurity solution vulnerable? This talk answers these questions through a sketch between two security experts: one presenting a vision on realizing AI-empowered security management solutions for next generation networks, the other challenging the solutions and recommending AI cybersecurity counter-measures.

Bio: Dhouha Ayed is a globally recognized expert in 5G and systems security with over 17 years of experience at Thales. Her academic background includes a PhD from Télécom Sud-Paris in 2005, an M.Sc., and an engineering degree in Computer Science. Prior to Thales, her research experience at Katholieke University of Leuven further solidified her foundation. As the technical coordinator of numerous European research projects, Dhouha has honed her expertise in designing cutting-edge security solutionsfor systems and future networks. Her leadership extends beyond research, as she actively participates in shaping the field through European working groups and standardization bodies like ETSI ZSM. Dhouha’s commitment to innovation continues at Thales’ new cortAIx laboratory, where she delves into the critical challenges facing future networks with the power of Artificial Intelligence.

Bio: Katarzyna Kapusta is a research engineer in cybersecurity at the Thales CortAIx Labs. She holds a PhD (2018) and M.Sc. (2014) degrees in Computer Science both from Télécom Paris (Paris, France), as well as a M.Sc. (2014) in Telecommunications from AGH University of Science and Technology (Cracow, Poland). Her research interests include data security, with a focus on data protection in distributed environments and security of Machine Learning. Currently, she is involved in PAROMA-MED and EDF STORE projects, where she provides her expertise on topics related to machine learning watermarking and secure federated learning. She is an active contributor to European standardization groups (ETSI Technical Committee Securing Artificial Intelligence, CEN/CENELEC WG’5) on the topic of secure Artificial Intelligence.

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Keynote #2

Title:  Self-sovereign Identity: a solid technology that meets the requirements of national digital identity management systems

Abstract: Nations are becoming increasingly interested in national digital identity management systems, especially since Covid-19, for mitigating frauds and providing electronic trust services. Several legislations are being introduced around the world, e.g. the eIDAS legislation in Europe, the Aadhaar Act in India. While identity management systems should facilitate electronic procedures and certain interactions, they must not undermine the privacy of individuals. The whole ecosystem is complex, with major issues at stake in terms of sovereignty, the economy and society as a whole. 

In this presentation, we will introduce the principles and motivations behind Self-Sovereign Identities (SSI), and show that SSIs have specific properties that can meet the needs of nations in managing national digital identities.

Bio: Maryline Laurent, PhD, works as a Full Professor at Télécom SudParis, Institut Polytechnique de Paris, France. She is head of the networks and cybersecurity department at Télécom SudParis and co-founder of the Institut Mines-Télécom’s “Values and policies of personal data” chair. She represents France on the IFIP TC11 committee on security and privacy. Her research focuses on cybersecurity and privacy, with a particular emphasis on privacy-enhancing technologies (PETs), for digital identity management services, the Internet of Things and cloud environments.

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Keynote #3

Title:  AI for biometrics 

Abstract: Biometrics has for objective the identification of individuals or their identity verification for cybersecurity purposes such as authentication. Using AI in such systems is not new for attacks or countermeasures. The fast evolution of Deep Neural Networks (DNN) for biometrics brings new trends, some of them are directly inherited by these models. This keynote has for main goal to illustrate the main issues for building cybersecurity solutions in biometrics. Practical applications will be given.

Bio: Christophe Rosenberger obtained his PhD in Information Technology from the University of Rennes 1 in 1999. His PhD thesis work was undertaken at ENSSAT in Lannion between 1996 and 1999 in the field of hyperspectral image processing. He joined the ENSI de Bourges school of engineering in Bourges (known now as INSA Centre Val de Loire) as associate professor in 2000. In 2007, he joined the ENSICAEN school of engineering in Caen as full professor. He is actually director of the GREYC research lab composed of 180 members. He belongs to the SAFE (Security, Architecture, Forensics, biomEtrics) research group in the GREYC research lab. His current work focuses in the domain of cybersecurity, in particular research activities in biometrics (keystroke dynamics, soft biometrics, evaluation of biometric systems, fingerprint quality assessment…) and digital forensics. He has authored or co-authored over 200 international publications and co-supervised 25 PhD thesis.