A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space. - Thibault Simonetto; Salijona Dyrmishi; Salah Ghamizi; Maxime Cordy; Yves Le Traon (IJCAI, 2022)

On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial Attacks. - Salijona Dyrmishi; Salah Ghamizi; Thibault Simonetto; Yves Le Traon; Maxime Cordy (SP, 2023)

Constrained Adaptive Attacks: Realistic Evaluation of Adversarial Examples and Robust Training of Deep Neural Networks for Tabular Data. - Thibault Simonetto; Salah Ghamizi; Antoine Desjardins; Maxime Cordy; Yves Le Traon (CoRR, 2023)

On the Impact of Industrial Delays when Mitigating Distribution Drifts: An Empirical Study on Real-World Financial Systems. - Thibault Simonetto; Maxime Cordy; Salah Ghamizi; Yves Le Traon; Clément Lefebvre; Andrey Boystov; Anne Goujon (DELTA, 2024)

Constrained Adaptive Attack: Effective Adversarial Attack Against Deep Neural Networks for Tabular Data. - Thibault Simonetto; Salah Ghamizi; Maxime Cordy (NeurIPS, 2024)

TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases. - Thibault Simonetto; Salah Ghamizi; Maxime Cordy (NeurIPS, 2024)

Enhancing Machine Learning Robustness for Critical Industrial Systems: Constrained Adversarial Attacks and Distribution Drift Solutions. - Thibault Simonetto (2024)

On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses. - Mohamed Djilani; Thibault Simonetto; Karim Tit; Florian Tambon; Paul Récamier; Salah Ghamizi; Maxime Cordy; Mike Papadakis (CoRR, 2025)

Insights on Adversarial Attacks for Tabular Machine Learning via a Systematic Literature Review. - Salijona Dyrmishi; Mohamed Djilani; Thibault Simonetto; Salah Ghamizi; Maxime Cordy (CoRR, 2025)