I started my academic career because I want to improve online privacy for everyone. While many researchers are motivated by theoretical or technical puzzles, my work is primarily driven by this societal concern.
Research Pillars đŹ
Preserving privacy is an ambitious, perhaps even too ambitious, goal. Privacy is a multifaceted issue that is difficult to fully apprehend. No single research project can address the complexity of online privacy on its own. To make this goal more tractable, I structure my research around three core pillars: attacking, enhancing, and deploying.
Attacking Privacy
The first step in addressing privacy issues is to identify them. This research pillar focuses on analyzing systems and schemes to uncover privacy vulnerabilities. In the cryptography community, attacks, or cryptanalysis, are an essential complement to the design of secure constructions. My objective is to extend this approach beyond cryptography and identify privacy vulnerabilities in a broader range of systems.
My early work focused on attacks against cryptographic schemes, and I have continued in this direction in subsequent work. In addition to cryptographic settings, I have also studied privacy issues in other systems, including machine learning models.
Enhancing Privacy
Following the identification of privacy issues, the next step is to mitigate them through the design of privacy-enhancing technologies (PETs). This pillar focuses on developing tools that enable meaningful computations on sensitive data while preserving privacy.
The design of cryptographic protocols has been a central part of my research, notably on multi-party computation (MPC). In addition, my work also covers non-cryptographic approaches such as differential privacy (DP). This range of approaches is a distinctive aspect of my research, as I try to identify and combine methods that can improve privacy guarantees in practice.
Deploying Privacy
Research on PETs has been active during the last two decades. While some tools, such as zero-knowledge proofs or encrypted databases, have reached a certain level of maturity, their adoption in real-world services remains limited. This gap suggests that the main challenges are not only technical. To achieve practical impact, privacy research must also account for human and societal factors.
This third pillar therefore focuses on the deployment of privacy technologies and the challenges that arise in practice. The goal is to study the factors that influence whether privacy solutions are adopted and how their guarantees may be weakened in real-world settings.
Publications đ
- M. Damie, M.B. Ertan, D. Essoussi, A. Makhanu, G. Peter, R. Wensveen, ‘TOSSS: a CVE-based Software Security Benchmark for Large Language Models’, 2026
- C. Gupta, N. Guldali, and M. Damie, ‘IoTLS 2.0: How Far Has IoT Industry Come in Securing Communications with TLS?’, EuroSec/EuroSys Workshops 2026
- M. Damie, and E. Cyffers, ‘Fedivertex: a Graph Dataset based on Decentralized Social Networks for Trustworthy Machine Learning’, WWW 2026
- M. Damie, F. Hahn, A. Peter, and J. Ramon, ‘Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning’, CODASPY 2026
- 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, ‘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’, SIMLA/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)