I am a member of several “PEPR Cybersécurité” projects:
I am the Inria’s PI (principal investigator) of the SecGen associated team with CISPA. This project is dedicated to synthetic data generation for intrusion detection systems.
I am currently co-supervising 5 PhD students:
I was also involved in various PhD:
Gimenez, P. F., & Mengin, J. (2024). Learning Conditional Preference Networks: an Approach Based on the Minimum Description Length Principle. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
Maxime Lanvin, Pierre-François Gimenez, Yufei Han, Frédéric Majorczyk, Ludovic Mé, et al.. Towards Understanding Alerts raised by Unsupervised Network Intrusion Detection Systems. The 26th International Symposium on Research in Attacks, Intrusions and Defenses (RAID 2023), Oct 2023, Hong Kong, France. ⟨10.1145/3607199.3607247⟩
Gimenez, Pierre-François & Mengin, Jérôme. (2023). Conditionally Acyclic CO-Networks for Efficient Preferential Optimization. 10.3233/FAIA230352.
Vincent Raulin, Pierre-François Gimenez, Yufei Han, Valérie Viet Triem Tong. BAGUETTE: Hunting for Evidence of Malicious Behavior in Dynamic Analysis Reports. 20th International conference on security and cryptography SECRYPT 2023, Jul 2023, Rome, Italy.
Lanvin, M., Gimenez, P. F., Han, Y., Majorczyk, F., Mé, L., & Totel, E. (2022, December). Errors in the CICIDS2017 dataset and the significant differences in detection performances it makes. In CRiSIS 2022-International Conference on Risks and Security of Internet and Systems.
Fabien Charmet, Harry Chandra Tanuwidjaja, Solayman Ayoubi, Pierre-François Gimenez, Yufei Han, Houda Jmila, Gregory Blanc, Takeshi Takahashi & Zonghua Zhang. Explainable artificial intelligence for cybersecurity: a literature survey. Ann. Telecommun. (2022).
Fargier, H., Gimenez, P. F., Mengin, J., & Le Nguyen, B. N. (2022, July). The complexity of unsupervised learning of lexicographic preferences. In 13th Multidisciplinary Workshop on Advances in Preference Handling (M-pref 2022)@ IJCAI 2022
Miranda, T. C., Gimenez, P. F., Lalande, J. F., Tong, V. V. T., & Wilke, P. (2022). Debiasing Android Malware Datasets: How can I trust your results if your dataset is biased?. IEEE Transactions on Information Forensics and Security.
Raulin, V., Gimenez, P. F., Han, Y., & Tong, V. V. T. (2022). Towards a Representation of Malware Execution Traces for Experts and Machine Learning. RESSI 2022-Rendez-Vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information.
Lanvin, M., Gimenez, P. F., Han, Y., Majorczyk, F., Mé, L., & Totel, É. (2022, May). Detecting APT through graph anomaly detection. In RESSI 2022-Rendez-Vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information.
Schoen, A., Blanc, G., Gimenez, P. F., Han, Y., Majorczyk, F., & Mé, L. (2022, May). Towards generic quality assessment of synthetic traffic for evaluating intrusion detection systems. In RESSI 2022-Rendez-Vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information.
Raulin, V., Gimenez, P. F., Han, Y., Viet Triem Tong, V., Ouairy, L. (2021). GUI-Mimic, a cross-platform recorder and fuzzer of Graphical User Interface. 9th GreHack Conference
Gimenez, P. F., Roux, J., Alata, E., Auriol, G., Kaâniche, M., & Nicomette, V. (2021). RIDS: Radio intrusion detection and diagnosis system for wireless communications in smart environment. ACM Transactions on Cyber-Physical Systems, 5(3), 1-1.
Bourdon, M., Gimenez, P. F., Alata, E., Kaaniche, M., Migliore, V., Nicomette, V., & Laarouchi, Y. (2020, November). Hardware-Performance-Counters-based anomaly detection in massively deployed smart industrial devices. In 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA) (pp. 1-8). IEEE.
Damien, A., Gimenez, P. F., Feyt, N., Nicomette, V., Kaâniche, M., & Alata, E. (2020, October). On-board Diagnosis: A First Step from Detection to Prevention of Intrusions on Avionics Applications. In 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE) (pp. 358-368). IEEE.
H Fargier, PF Gimenez, J Mengin - Journal of Universal Computer Science, 2020
Pierre-François Gimenez. Apprentissage de préférences en espace combinatoire et application à la recommandation en configuration interactive. Intelligence artificielle [cs.AI]. Université Paul Sabatier - Toulouse III, 2018. Français. ⟨NNT : 2018TOU30182⟩. ⟨tel-02303275⟩
Fargier, H., Gimenez, P. F., & Mengin, J. (2018, April). Learning lexicographic preference trees from positive examples. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 32, No. 1).
Fargier, H., Gimenez, P. F., & Mengin, J. (2016, September). Recommendation for product configuration: an experimental evaluation. In 18th International Configuration Workshop (CWS 2016) within CP 2016: 22nd International Conference on Principles and Practice of Constraint Programming (pp. pp-9).