Paper presented at EvoApplications 2026 (Toulouse) on an evolutionary-ML approach building lightweight probabilistic surrogates for cyber-attack detection on edge devices in Water Distribution Networks.
2025.09.0115h course — APP-ING3 level (S9) — machine learning for anomaly detection, end-to-end forensic case study, adversarial machine learning.
2025.09.01Journal article (SoftwareX) presenting GPML, an open-source library that transforms raw network traffic into graph representations for community and spectral-metric-based cyberattack detection.
2025.09.0123h course — APPING-2 level (S7) — machine learning for security operations, language models for security, ethics and securing AI.
GPML has for purpose to give an easy to use tool to ready data for use to machine learning algorithm using graph modelisation to compute new features and insert them to pandas dataframe. It also comes with a module with one ready function to use to convert dataset to html graph representation.
12h course — ING1 level (S6) — trusted AI, explainability of tree-based algorithms, adversarial exploratory attacks.