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ORCIDJean-Philippe Bossuat
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2020 – today
- 2024
[i10]Jean-Philippe Bossuat, Rosario Cammarota, Jung Hee Cheon, Ilaria Chillotti, Benjamin R. Curtis, Wei Dai, Huijing Gong, Erin Hales, Duhyeong Kim, Bryan Kumara, Changmin Lee, Xianhui Lu, Carsten Maple, Alberto Pedrouzo-Ulloa, Rachel Player, Luis Antonio Ruiz Lopez, Yongsoo Song, Donggeon Yhee, Bahattin Yildiz:
Security Guidelines for Implementing Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2024: 463 (2024)- [i9]Jean-Philippe Bossuat, Anamaria Costache, Christian Mouchet, Lea Nürnberger, Juan Ramón Troncoso-Pastoriza:
Practical q-IND-CPA-D-Secure Approximate Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2024: 853 (2024) - 2023
- [j4]Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Privacy-Preserving Federated Recurrent Neural Networks. Proc. Priv. Enhancing Technol. 2023(4): 500-521 (2023) - [c5]Francesco Intoci, Sinem Sav, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference. ACNS Workshops 2023: 359-377 - [c4]David Froelicher, Hyunghoon Cho, Manaswitha Edupalli, Joao Sa Sousa, Jean-Philippe Bossuat, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, Bonnie Berger, Jean-Pierre Hubaux:
Scalable and Privacy-Preserving Federated Principal Component Analysis. SP 2023: 1908-1925 - [i8]David Froelicher, Hyunghoon Cho, Manaswitha Edupalli, Joao Sa Sousa, Jean-Philippe Bossuat, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, Bonnie Berger, Jean-Pierre Hubaux:
Scalable and Privacy-Preserving Federated Principal Component Analysis. CoRR abs/2304.00129 (2023) - [i7]Francesco Intoci, Sinem Sav, Apostolos Pyrgelis, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
slytHErin: An Agile Framework for Encrypted Deep Neural Network Inference. CoRR abs/2305.00690 (2023) - 2022
- [j3]Sinem Sav, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Manfred Claassen, Jean-Pierre Hubaux:
Privacy-preserving federated neural network learning for disease-associated cell classification. Patterns 3(5): 100487 (2022) - [c3]Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation. ACNS 2022: 521-541 - [i6]Sinem Sav, Abdulrahman Diaa, Apostolos Pyrgelis, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Privacy-Preserving Federated Recurrent Neural Networks. CoRR abs/2207.13947 (2022) - [i5]Juan Ramón Troncoso-Pastoriza, Alain Mermoud, Romain Bouyé, Francesco Marino, Jean-Philippe Bossuat, Vincent Lenders
, Jean-Pierre Hubaux:
Orchestrating Collaborative Cybersecurity: A Secure Framework for Distributed Privacy-Preserving Threat Intelligence Sharing. CoRR abs/2209.02676 (2022) - [i4]Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation. IACR Cryptol. ePrint Arch. 2022: 24 (2022) - 2021
- [j2]David Froelicher, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao Sa Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Scalable Privacy-Preserving Distributed Learning. Proc. Priv. Enhancing Technol. 2021(2): 323-347 (2021) - [j1]Christian Mouchet, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Multiparty Homomorphic Encryption from Ring-Learning-with-Errors. Proc. Priv. Enhancing Technol. 2021(4): 291-311 (2021) - [c2]Jean-Philippe Bossuat, Christian Mouchet, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-sparse Keys. EUROCRYPT (1) 2021: 587-617 - [c1]Sinem Sav, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux:
POSEIDON: Privacy-Preserving Federated Neural Network Learning. NDSS 2021 - 2020
- [i3]David Froelicher, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Sinem Sav, Joao Sa Sousa, Jean-Philippe Bossuat, Jean-Pierre Hubaux:
Scalable Privacy-Preserving Distributed Learning. CoRR abs/2005.09532 (2020) - [i2]Sinem Sav, Apostolos Pyrgelis, Juan Ramón Troncoso-Pastoriza, David Froelicher, Jean-Philippe Bossuat, Joao Sa Sousa, Jean-Pierre Hubaux:
POSEIDON: Privacy-Preserving Federated Neural Network Learning. CoRR abs/2009.00349 (2020) - [i1]Jean-Philippe Bossuat, Christian Mouchet, Juan Ramón Troncoso-Pastoriza, Jean-Pierre Hubaux:
Efficient Bootstrapping for Approximate Homomorphic Encryption with Non-Sparse Keys. IACR Cryptol. ePrint Arch. 2020: 1203 (2020)
Coauthor Index
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