Current status đŤ
I have obtained a Ph.D. in Applied Cryptography (titled Privacy-Preserving Computations on Sparse Data) in December 2025. As I finish my Ph.D., I am slowly starting to transition into industry. My goal is to find an unusual position at the intersection of academia and industry in order to build and deploy real-world privacy-enhancing technologies.
Research Interests đŹ
I am interested in any privacy-enhancing technology. So far, I have worked on multiparty computation, searchable encrypted, and federated learning, but I am not attached to these primitives. My only motivation is to find real-world privacy problems, and to solve them using the best solutions.
If ever you are an non-profit organization and need support from a privacy engineer/researcher, please reach out to me! In the upcoming years, I am willing to dedicate part of my time to pro-bono research & development.
Besides these technical interests, I am open to many other topics. Especially, I am looking forward to any insights on ethics or environmental evaluation of computer systems. These elements essentially contribute to my personal reflections about my long-term role as a computer scientist in world facing multiple crisis.
Publications đ
- M. Damie, and E. Cyffers, ‘Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning’, 2025
- M. Damie, M. Pop, and M. Posthuma, ‘Energy Consumption of TLS, Searchable Encryption and Fully Homomorphic Encryption’, FPS 2025
- M. Damie, F. Mazzone, F. Hahn, A. Peter, and J. Ramon, ‘Noisy Function Secret Sharing and its applications to Differentially Private computations’, 2025
- M. Damie, F. Hahn, A. Peter, and J. Ramon, ‘DDH-based schemes for multi-party Function Secret Sharing’, NordSec 2025
- M. Damie, F. Hahn, A. Peter, and J. Ramon, ‘Eliminating Exponential Key Growth in PRG-Based Distributed Point Functions’, DPM/ESORICS Workshops 2025
- M. Damie, F. Hahn, A. Peter, and J. Ramon, ‘Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning’, 2025
- M. Damie, F. Hahn, A. Peter, and J. Ramon, ‘How to Securely Shuffle? A survey about Secure Shufflers for privacy-preserving computations’, 2025
- B. van Dartel, M. Damie, and F. Hahn, ‘Evaluating Membership Inference Attacks in heterogeneous-data setups’, ACNS Workshops 2025
- M. Damie, J.-B. Leger, F. Hahn and A. Peter, ‘Revisiting the Attackerâs Knowledge in Inference Attacks Against Searchable Symmetric Encryption’, ACNS 2025
- M. Dijsklag, M. Damie, F. Hahn and A. Peter, ‘Passive query-recovery attack against secure conjunctive keyword search schemes’, ACNS 2022
- M. Damie, F. Hahn, and A. Peter, âA Highly Accurate Query-Recovery Attack against Searchable Encryption using Non-Indexed Documentsâ, USENIX Security 21
Awards & Honors đ
- Young Talents in Cybersecurity 2025, co-organized by the French Embassy in The Netherlands and the Dutch Embassy in France.
- Distinguished Artifact Reviewer at PETS 2025.
- Nomination for the Dutch CyberSecurity Research Paper (i.e. top 3) with the paper âA Highly Accurate Query-Recovery Attack against Searchable Encryption using Non-Indexed Documentsâ
Service
- Sub-reviews: CCS 2024, PETS 2023, CODASPY 2022
- Program committee: NDSS Artifact Evaluation 20{24,25}, PETS Artifact Evaluation 20{24,25}, USENIX Security Poster (2024)
- Student representative at the University of Technology of Compiègne: Board of directors (2017-2021), CS department (2018-2019), Humanities department (2017-2019)