CV
Education and work experience
- Since 2020: Associate professor in cybersecurity
- CentraleSupélec and Inria (Rennes, France)
- Intrusion detection and malware analysis
- 2018–2020: Postdoc in cybersecurity
- LAAS-CNRS (Toulouse, France)
- Intrusion detection based on machine learning
- 2015–2018: PhD in artificial intelligence
- IRIT (Toulouse, France)
- Preferences learning and application to e-commerce
Experience
Research projects
I am a member of several “PEPR Cybersécurité” projects:
- Superviz, on supervision for security
- DefMal, on defense against malware
- REV, on vulnerability identification and exploitation
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.
Doctoral advisor
I am currently co-supervising three PhD students:
- Maxime Lanvin on unsupervised intrusion detection in networks (with Ludovic Mé, Grégory Blanc, Yufei Han and Frédéric Majorczyk)
- Vincent Raulin on dynamic malware analysis (with Valérie Viet Triem Tong and Yufei Han)
- Adrien Schoen on network packets generation for IDS evaluation (with Ludovic Mé, Éric Totel, Yufei Han and Frédéric Majorczyk)
I was also involved in various PhD:
- Malcolm Bourdon, defended in 2021
- Aliénor Damien, defended in 2020
- Jonathan Roux, defended in 2020
Scientific events and dissemination
- “Hands-on machine learning for security” event, sponsored by the “GDR Sécurité Informatique”
- Seminars of the CIDRE team (https://team.inria.fr/cidre/research/seminars/) since 2020 (about 50 talks)
- Doctoral paper reading group “Papers Please” (https://team.inria.fr/cidre/papers-please/) since 2022
- Youtube page of the team (https://www.youtube.com/@cidre-team) since 2020
- Various scientific events in the team
PC member and reviewer
Security conferences
- EICC 2023
- THCon 2022, 2023
- DSN 2022
- EICC 2021
- Doctoral Forum of DSN 2020
- ISSRE 2020
Artificial intelligence conferences
- AAAI 2021, 2022
- IJCAI 2020
- RJCIA 2019, 2020
Journals
- IEEE Network
- Transactions on Computers
- International Journal of Information Security
- Computers & Security
- Journal of Computer Security
Publications
Errors in the CICIDS2017 dataset and the significant differences in detection performances it makes
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.
Explainable artificial intelligence for cybersecurity: a literature survey
Charmet, F., Tanuwidjaja, H.C., Ayoubi, S. et al. Explainable artificial intelligence for cybersecurity: a literature survey. Ann. Telecommun. (2022).
The complexity of unsupervised learning of lexicographic preferences
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
Debiasing Android Malware Datasets: How can I trust your results if your dataset is biased?
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.
Towards a Representation of Malware Execution Traces for Experts and Machine Learning
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.
Detecting APT through graph anomaly detection
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.
Towards generic quality assessment of synthetic traffic for evaluating intrusion detection systems
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.
GUI-Mimic, a cross-platform recorder and fuzzer of Graphical User Interface
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
RIDS: Radio intrusion detection and diagnosis system for wireless communications in smart environment
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.
Hardware-Performance-Counters-based anomaly detection in massively deployed smart industrial devices
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.
On-board Diagnosis: A First Step from Detection to Prevention of Intrusions on Avionics Applications
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.
Experimental evaluation of three value recommendation methods in interactive configuration
H Fargier, PF Gimenez, J Mengin - Journal of Universal Computer Science, 2020
Apprentissage de préférences en espace combinatoire et application à la recommandation en configuration interactive
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⟩
Learning lexicographic preference trees from positive examples
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).
Recommendation for product configuration: an experimental evaluation (Best paper award)
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).