Secure computation allows multiple parties to compute functions over their private inputs without revealing anything beyond the output. My thesis focuses on "on-the-fly" secure computation: protocols that require minimal interaction between parties and no special setup assumptions, making them ideal for real-world deployments. The work provides new theoretical frameworks and practical implementations that advance both the theory and practice of secure computation.
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Slides
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On Compressing Linearly Shared Correlations
Geoffroy Couteau, Alexander Koch, Nikolas Melissaris, Peter Scholl, Sacha Servan-Schreiber, and Xiaxi Ye
TCC 2026
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Client-Server Homomorphic Secret Sharing in the CRS Model
Damiano Abram, Geoffroy Couteau, Lalita Devadas, Aditya Hegde, Abhishek Jain, Lawrence Roy, and Sacha Servan-Schreiber
Eurocrypt 2026
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Concretely-Efficient Multi-Key Homomorphic Secret Sharing and Applications
Kaiwen He, Sacha Servan-Schreiber, Geoffroy Couteau, and Srinivas Devadas
S&P 2026
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Pseudorandom Correlation Functions for Garbled Circuits
Geoffroy Couteau, Srinivas Devadas, Alexander Koch, and Sacha Servan-Schreiber
TCC 2025
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Non-Interactive Distributed Point Functions
Elette Boyle, Lalita Devadas, and Sacha Servan-Schreiber
PKC 2025
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Multi-Key Homomorphic Secret Sharing
Geoffroy Couteau, Lalita Devadas, Aditya Hegde, Abhishek Jain, and
Sacha Servan-Schreiber
Eurocrypt 2025
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Simultaneous-Message and Succinct Secure Computation
Elette Boyle, Abhishek Jain, Sacha Servan-Schreiber, and Akshayaram Srinivasan
Eurocrypt 2025
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Designing Hardware for Cryptography and Cryptography for Hardware
Srini Devadas, Simon Langowski, Nikola Samardzic, Sacha Servan-Schreiber, and Daniel Sanchez
CCS 2022 (invited talk paper)
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ShorTor: Improving Tor Network Latency via
Multi-hop Overlay Routing
Kyle Hogan, Sacha Servan-Schreiber, Zachary Newman, Ben Weintraub, Cristina Nita-Rotaru, and Srini Devadas
S&P 2022
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Private Approximate Nearest Neighbor Search with Sublinear Communication
Sacha Servan-Schreiber, Simon Langowski, and Srini Devadas
S&P 2022
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Spectrum: High-Bandwidth Anonymous Broadcast
Zachary Newman, Sacha Servan-Schreiber, and Srini Devadas
NSDI 2022