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In the course of 2021, 42% of Belgian companies suffered a cyber attack. Those targeting citizens are no less numerous: more than 4.5 million suspicious messages have been sent to Safeonweb, the government body responsible for informing Belgian citizens about computer security. More than ever, at a time when the geopolitical context reinforces the threat of a cyberwar, how can we cope? Jean-Noël Colin, cybersecurity expert, professor at the Faculty of Computer Science of UNamur and member of the NaDI Institute, gives us an explanation.

The Namurians of the Year for 2022 are known! Organised by the ASBL "Namurois de l'année" in partnership with the magazine AlluMeuse, the "Namurois de l'année" ceremony has just unveiled the Namur personalities who have distinguished themselves over the past year. And among them, in the science category, we find Anthony Cleve, professor in the Faculty of Computer Science.

The Ten-years Most Influential Paper award has just been presented to three members of UNamur's Faculty of Computer Science: Xavier Devroey, Gilles Perrouin and Maxime Cordy. The award recognizes the paper published ten years previously that has had the greatest impact on the research community. It was awarded at the 18th edition of the International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS '24), which took place in early February in Bern, Switzerland..

Gilles Perrouin has just received the award for the most influential paper at the SPLC2024 conference. This award highlights a successful line of research on software product line testing, already awarded in February 2024.

Space has become a major economic and strategic issue. As a member of the European UNIVERSEH Alliance, UNamur explores this space theme in its various departments, from physics to geology, via mathematics, computer science or philosophy. Without forgetting to address the general public, who still dream of the stars...

The workshop will feature:A keynote presentation on public value and AI implementation at VRT.Sessions on discoverability, user agency, and explainability.Discussions on regulation, including perspectives on the AI Act and transparency in media.An interactive session showingcasing AI-driven prototypes.The event will also highlight our project's latest findings. Join us for a day of thought-provoking discussions, knowledge exchange, and networking opportunities!Would you like to attend? Places are limited and will be allocated on a first-come, first-served basis, so register as soon as possible. Registration will close on April 11, 2025. More information here

Can a computer learn a language like a child? A recent study published in the leading journal Computational Linguistics by Professors Katrien Beuls (Université de Namur) and Paul Van Eecke (AI-lab, Vrije Universiteit Brussel) sheds new light on this question. The researchers argue for a fundamental revision of the way artificial intelligence acquires and processes language.

SynopsisA honeypot is a security tool deliberately designed to be vulnerable, thereby enticing attackers to probe, exploit, and compromise it. Since their introduction in the early 1990s, honeypots have remained among the most widely used tools for capturing cyberattacks, complementing traditional defenses such as firewalls and intrusion detection systems. They serve both as early warning systems and as sources of valuable attack data, enabling security professionals to study the techniques and behaviors of threat actors.While conventional honeypots have achieved significant success, they remain deterministic in their responses to attacks. This is where adaptive or intelligent honeypots come into play. An adaptive honeypot leverages Machine Learning techniques, such as Reinforcement Learning, to interact with attackers. These systems learn to take actions that can disrupt the normal execution flow of an attack, potentially forcing attackers to alter their techniques. As a result, attackers must find alternative routes or tools to achieve their objectives, ultimately leading to the collection of more attack data.Despite their advantages, traditional honeypots face two main challenges. First, emulation-based honeypots (also known as low- and medium-interaction honeypots) are increasingly susceptible to detection, which undermines their effectiveness in collecting meaningful attack data. Second, real-system-based honeypots (also known as high-interaction honeypots) pose security risks to the hosting organization if not properly isolated and protected. Since adaptive honeypots rely on the same underlying systems, they also inherit these challenges.This thesis investigates whether it is possible to design a honeypot system that mitigates these challenges while still fulfilling its primary objective of collecting attack data. To this end, it proposes a new abstract model for adaptive self-guarded honeypots, designed to balance attack data collection, detection evasion, and security preservation, ensuring that it does not pose a risk to the rest of the network.Jury membersProf. Wim VANHOOF, President, University of NamurProf. Jean-Noël COLIN, Promoter, University of NamurProf. Florentin ROCHET, Internal Member, University of NamurProf. Benoît FRENAY, Internal Member, University of NamurProf. Ramin SADRE, External Member, Catholic University of LeuvenDr. Jérôme FRANCOIS, External Member, University of LuxembourgYou are cordially invited to a drink, which will follow the public defense. For good organization, please give your answer by Tuesday, May 20, 2025. I want to register

Synopsis deep learning methods have become increasingly popular for building intelligent systems. Currently, many deep learning architectures constitute the state of the art in their respective domains, such as image recognition, text generation, speech recognition, etc. The availability of mature libraries and frameworks to develop such systems is also a key factor in this success.This work explores the use of these architectures to build intelligent systems for sign languages. The creation of large sign language data corpora has made it possible to train deep learning architectures from scratch. The contributions presented in this work cover all aspects of the development of an intelligent system based on deep learning. A first contribution is the creation of a database for the Langue des Signes de Belgique Francophone (LSFB). This is derived from an existing corpus and has been adapted to the needs of deep learning methods. The possibility of using crowdsourcing methods to collect more data is also explored.The second contribution is the development or adaptation of architectures for automatic sign language recognition. The use of contrastive methods to learn better representations is explored, and the transferability of these representations to other sign languages is assessed.Finally, the last contribution is the integration of models into software for the general public. This led to a reflection on the challenges of integrating an intelligent module into the software development life cycle.Jury membersProf. Wim VANHOOF, President, University of NamurProf. Benoît FRENAY, Promoter, University of NamurProf. Anthony CLEVE, Co-promoter, University of NamurProf. Laurence MEURANT, Internal Member, University of NamurProf. Lorenzo BARALDI, External Member, University of ModenaProf. Annelies BRAFFORT, External Member, University of Paris-SaclayProf. Joni DAMBRE, External Member, University of GhentYou are cordially invited to a drink, which will follow the public defense. For a good organization, please give your answer by Friday June 6. I want to register

A choir of robots sounds like science fiction! Yet it is a reality at the University of Namur. In the robotics laboratory of the Faculty of Computer Science, researchers from the naXys institute, led by professors Elio Tuci and Timoteo Carletti, some members of TRAKK, some artists and external partners collaborated on the "Synthetic Choirs" project.

Floriane Goosse, a PhD student at the University of Namur, within the NaDI-CeRCLe research center, has received the prestigious "Best Research Paper Award" for her thesis paper conducted in collaboration with Wafa Hammedi, professor in the Department of Management at UNamur, and Dominik Mahr, from Maastricht University.

How can teleworking and face-to-face work be reconciled? How can these professional practices be framed to reinforce the innovative and sustainable dimensions of hybrid work? These are the questions that Michel Ajzen, a specialist in organizational management, is tackling as part of his teaching assignments in the Department of Management Sciences at UNamur. His research focuses on hybrid work and organizational innovation, with a transdisciplinary approach aimed at reinventing managerial practices to meet contemporary challenges.