Le 07/03/2022 à 09:30, M. Raphaël LARSEN, Département ITI – laboratoire LATIM soutiendra publiquement ses travaux en vue de l’obtention du grade de “Docteur d’IMT Atlantique”. Vous trouverez le streaming en direct et l’enregistrement ici : https://youtu.be/1rt1cwH8yFY
Co-organisé par la chaire / Marc-Oliver Pahl : Le Jeudi 31 mars 2022 de 9h à 16h15 le 15e Colloque scientifique de l’IMT se tient place à l’Institut Mines-Télécom – Palaiseau (91). Participez et découvrez les travaux récents et les avancées scientifiques sur la gestion de crise et la cybersécurité, menés par les équipes de recherche des écoles de l’IMT et de leurs partenaires.
La chaire cyberCNI.fr présentera ses travaux sur la réalité mixte et le cyber et notre testbed. Plusieurs des nos doctorants vont présenter leurs travaux. Vous pouvez suivre sur place ou en ligne – donc n’hésitez pas de vous inscrire!
Being part of the wonderful cybersecurity ecosystem in Brittany, we visited the ENSIBS and their excellent cybersecurity crisis management exercise. We used the visit not only to get impressed but also to make contact with potential future PhDs and PostDocs at the chaire, and of course to discuss joint research and teaching. Thanks a lot for the invitation!
Europe’s cybersecurity and cyberdefense community met in Rennes for the 6th edition of the European Cyber Week (ECW) from Nov 16-18, 2021. Together with our chairholder Marc-Oliver Pahl, Léo Lavaur, Anthony David, and Nicolas Delcombel, three of our PhD students, presented a demo on our research line covering Virtual Reality interfaces for improving human-machine communication in cybersecurity.
On Sep 21, 2021, we had the pleasure to visit our partner EDF in Paris Palaiseau. Today, Mariana present her work. In her talk, she will explain how to make control of cyber-physical systems resilent, using switched linear control system.
On Sep 21, 2021, we had the pleasure to visit our partner EDF in Paris Palaiseau! Here is another highlight presentation:
Hassan CHAITOU, Security risk optimization for learning on heterogeneous quality data
A classifier is a component used in the automation of “decision-making” or complex data abstraction: intruder detection, speed limitation extraction. For an efficient classifier, the training must be on a large volume of data and be renewed over time by integrating or revoking certain learning data. From a security point of view, this process represents a risk since it offers the attacker various ways of degrading classifier performance (either by forcing classifications mischievous, either by randomly degrading its performance). These two types of attacks require more or less effort from the attacker.
This risk is exacerbated when data comes from sources (network equipment, organizations) corresponding to heterogeneous trust levels. Hassan’s thesis aims at controlling the risk associated with this update via game theory in the case where the confidence in the learning data is not homogeneous.
On Sep 21, 2021, we had the pleasure to visit our partner EDF in Paris Palaiseau! Here is another highlight presentation:
Julius BÜNGER, Keeping software in massive IoT installations up-to-date
Julius’s thesis will provide solutions to ease the IoT device recycling. An object may become unusable for several reasons, for example a hardware failure, no more energy from the battery or obsolete functions. In that case, it is important to decommission the device, and recycle it. One solution for recycling is to re-use the object in a different application or deployment, if it embeds the necessary functions. It can also be disassembled and its parts can be sent to different recycling industry. In order to make this possible, we need to address the issues of localization, keep-alive,classification and security.
On Sep 21, 2021, we had the pleasure to visit our partner EDF in Paris Palaiseau! Here is another highlight presentation:
Awaleh HOUSSEIN MERANEH, Automated learning and handling of Cyber-Physical Attacks
Awaleh’s study focuses on industrial control systems, which are one of the applications of cyber-physical systems. The major goal of his thesis is to use side channel leakage parameters to detect abnormalities (system failure, cyber-attacks) in industrial control systems. These leakage parameters include things like sound, power usage, electromagnetic, and so on. Review the existing sound anomaly detection methods for ICS in the literature, and to then propose our own sound anomaly detection approach.
On Sep 21, 2021, we had the pleasure to visit our partner EDF in Paris Palaiseau! Here is another highlight presentation:
Léo LAVAUR, Federated learning for defending Cyber-Attacks
In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative Machine Learning (ML). FL does not share local data but ML models, offering applications in diverse domains, including cybersecurity. Léo explains how FL has been studied to overcome challenges of collaborative intrusion detection and mitigation systems. His current research focuses on applying these concepts to specific use cases, such as smart factories, autonomous vehicles, or smart healthcare.
On Dec 13, 2021, we had the pleasure to welcome the Member of Parliament Florian Bachelier and a high decorated delegation from Airbus Cybersecurity, consisting of Nicolas Razy, Head of Defence and Strategic Programmes France, Serge Maurice, Directeur des relations opérationnelles et Défense, Eric CHAMBAREAU, Directeur Engineering France & CyberEntrainement chez Airbus CyberSecurity, Laureline Kiss, HR Business Partner chez Airbus CyberSecurity, Frédéric Dubois, Head of Rennes Airbus Cybersecurity offices.
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