In our next ROC seminar, the PhD students will present their current work on Tuesday, 28 October 2025, at a time to be announced (TBA). Each presentation will last 15 minutes.
Seminar Location: Room Number: TBA, CNAM, Paris, France
Speaker: Zeidan Braik
Title: TBA
Bio: TBA
Abstract: TBA
Speaker: Thierry N’kouka
Title: Traffic Prediction Improvement in 5G and beyond: AI and Self-Controlled Components
Bio: Thierry N’Kouka holds a master’s degree in computer networks and IoT Systems from the Conservatoire National des Arts et Métiers (Cnam) in Paris and is currently pursuing a PhD in Distributed Artificial Intelligence for IoT Architectures. His research focuses on leveraging distributed AI to design sustainable and scalable solutions for managing the growing complexity and demands of interconnected smart systems in IoT. It aims to address challenges such as device heterogeneity, resource constraints, and scalability.
Abstract: The advent of 5G and Beyond 5G (B5G) networks requires novel network management strategies to mitigate potential congestion. Traditional reactive approaches are inadequate as they address issues only post-occurrence, whereas proactive Artificial Intelligence (AI) powered methods can predict and optimize resource allocation. This paper leverages AI on 5G emulated datasets to forecast network traffic, facilitating proactive resource allocation. The experimental results however indicate suboptimal model performance due to the high variability, irregular patterns, sudden traffic bursts, noise, and inconsistent data distributions in the datasets. Our analysis revealed that these issues arise from uncoordinated background traffic, system operations, and random traffic-consuming activities, leading to underperforming model outcomes. Given these challenges, we have proposed a Self-Controlled Component (SCC)-based approach to ensure that high-quality data focused on user-origin traffic is fed into the selected AI models, thereby improving prediction accuracy and enhancing performance.
Publication: Thierry Isaac N’kouka, Tatiana Aubonnet, Frédéric Lemoine, Mounir Kellil, Noëmie Simoni. Traffic Prediction Improvement in 5G and beyond: AI and Self-Controlled Components. 2025 12th IFIP International Conference on New Technologies, Mobility and Security (NTMS), Jun 2025, Paris, France. pp.213-216, 10.1109/NTMS65597.2025.11076981. hal-05172767
Speaker: Davide Avesani
Title: TBA
Bio: TBA
Abstract: TBA
Speaker: Jacopo Bufalino
Title: Inside Job: Defending Kubernetes Clusters Against Network Misconfigurations
Bio: Jacopo is a security researcher working on cloud and supply chain security. He is also a doctoral candidate at Aalto University.
Abstract: Kubernetes has emerged as the de facto standard for container orchestration. Unfortunately, its increasing popularity has also made it an attractive target for malicious actors. Despite extensive research on securing Kubernetes, little attention has been paid to the impact of network configuration on the security of application deployments. This paper addresses this gap by conducting a comprehensive analysis of network misconfigurations in a Kubernetes cluster with specific reference to lateral movement. Accordingly, we carried out an extensive evaluation of 287 open-source applications belonging to six different organizations, ranging from IT companies and public entities to non-profits. As a result, we identified 634 misconfigurations, well beyond what could be found by solutions in the state of the art. We responsibly disclosed our findings to the concerned organizations and engaged in a discussion to assess their severity. As of now, misconfigurations affecting more than thirty applications have been fixed with the mitigations we proposed.
Publication: Jacopo Bufalino, Jose Luis Martin Navarro, Mario Di Francesco, Tuomas Aura. Inside Job: Defending Kubernetes Clusters Against Network Misconfigurations. CoNEXT, Dec 2025, 10.1145/3749220. hal-05230013
