Search results

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.

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.

A delegation from the Université de Namur took part in an exploratory mission to the Université Cheikh Anta Diop (UCAD) in Dakar, Senegal. The aim: to discover the research carried out in the field, meet UCAD researchers and initiate future collaborations between the two institutions.

Nathalie Burnay, professor in the EMCP Faculty and member of the TRANSITIONS Institute, has just been awarded PDR funding from the F.R.S-FNRS for her BRIDGE-EXT project. In collaboration with the Haute Ecole de Travail Social de Lausanne, she will focus on the situations and reasons that contribute to the continuation of professional activity after the legal retirement age.

The program Interventions by experts and researchers in the field of data science, , AI, digital twins, digital law and participatory processes.Registrations on the Vivre la Ville... website.

Reconciling family life and a political career in the European Parliament poses major challenges, particularly for MEPs with young children. This is demonstrated by Elena Frech, researcher at the University of Namur, in her recent research on work-life balance in European institutions.

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...

"A social-democratic phoenix? The trajectories of social democracy after the eurozone crisis."

An analysis of voter turnout in October 2024This analysis presents a comparison of voter turnout in Wallonia, Brussels and Flanders. On the one hand, the report identifies the profiles and political attitudes of voters who abstained (representative survey of the Belgian population). On the other hand, the report presents the evolution of abstention and electoral participation according to institutional and political contexts in Wallonia. Particular attention is paid to the increase in blank and invalid votes in Wallonia.Analysis of the effects of electoral reforms since 2018This analysis presents the effects linked to the adoption of gender quotas in communal executives, as well as the effects of the end of the devolutive effect of the top box in Wallonia. These electoral reforms may have had limited effects in some communes (mainly due to a "learning" effect of the new electoral rules). Our report analyzes the effects observed in 2024 and the factors explaining the differences observed between Wallonia's communes.Analysis of the restructuring of the electoral offer in 2024While 2018 had seen a significant increase in the number of lists present at communal polls (notably so-called "citizen" and far-right lists), in October 2024, the number of lists in competition fell significantly. An analysis of official figures describes the evolution of the number and type of lists according to the institutional and political configurations of Wallonia's communes. It focuses in particular on the evolution of typically "local" lists, a Walloon characteristic within European democracies. Practical information L'ArsenalRue Bruno, 11 - 5000 NamurL'Arsenal is a 10-minute walk from Namur train station and the Parliament of Wallonia. Adjacent parking is available free of charge (Rue de l'Arsenal 13, 5000 Namur)Registration required (places are limited - registration deadline: March 3) Program 9:00-13:00: Conference workshop9:00-9:30: welcome and coffee9:30-9:35: presentation of the project by the inter-university consortium9:35-11:40 : presentation of reports and Q&A Analysis of the restructuring of the electoral offer in 2024 Analysis of electoral participation in 2024 Analysis of the effects of electoral reforms in 202411:40-11:50 : closing remarks12:00-13:00: closing lunchContact person For information requests: laura.uyttendaele@unamur.be and jeremy.dodeigne@unamur.be SPW Interior and Social Action

Arthur Borriello, professor in the EMCP Faculty and member of the TRANSITIONS Institute, has just been awarded a Mandat d'Impulsion Scientifique (MIS), prestigious funding from the F.R.S-FNRS. Through a comparison of 4 countries, this research project aims to understand why and how social democratic parties have adapted to the socio-political changes of the last ten years. Explanations.

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.

In recent decades, electoral reforms have strengthened the individual dimension of elected representatives in proportional representation (PR) electoral systems. This general trend towards the "personalization of political life" is leading researchers to study its effects on intra-partisan competition.