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2020 – today
- 2024
[c3]Itamar Zimerman, Moran Baruch, Nir Drucker, Gilad Ezov, Omri Soceanu, Lior Wolf:
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption. ICML 2024- 2023
- [j4]Ehud Aharoni
, Allon Adir, Moran Baruch, Nir Drucker, Gilad Ezov, Ariel Farkash, Lev Greenberg, Ramy Masalha, Guy Moshkowich, Dov Murik, Hayim Shaul, Omri Soceanu:
HeLayers: A Tile Tensors Framework for Large Neural Networks on Encrypted Data. Proc. Priv. Enhancing Technol. 2023(1): 325-342 (2023) - [c2]Ehud Aharoni, Nir Drucker, Gilad Ezov, Eyal Kushnir, Hayim Shaul, Omri Soceanu:
Poster: Efficient AES-GCM Decryption Under Homomorphic Encryption. CCS 2023: 3567-3569 - [i7]Moran Baruch, Nir Drucker, Gilad Ezov, Eyal Kushnir, Jenny Lerner, Omri Soceanu, Itamar Zimerman:
Sensitive Tuning of Large Scale CNNs for E2E Secure Prediction using Homomorphic Encryption. CoRR abs/2304.14836 (2023) - [i6]Itamar Zimerman, Moran Baruch, Nir Drucker, Gilad Ezov, Omri Soceanu, Lior Wolf:
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption. CoRR abs/2311.08610 (2023) - [i5]Ehud Aharoni, Nir Drucker, Gilad Ezov, Eyal Kushnir, Hayim Shaul, Omri Soceanu:
E2E near-standard and practical authenticated transciphering. IACR Cryptol. ePrint Arch. 2023: 1040 (2023) - 2022
- [j3]George Bravos, Antonio J. Cabrera, Camilo Correa, Dragan Danilovic, Nikolaos Evangeliou, Gilad Ezov, Zoran Gajica, Dusan Jakovetic, Leonidas Kallipolitis, Milan Lukic, Julien-Etienne Mascolo, Davide Masera, Raúl Mazo, Ivan Mezei, Andreas I. Miaoudakis, Nemanja Milosevic, William Oliff, Jacques Robin, Michail Smyrlis, Georgia Sakellari, Giorgos Stamatis, Dusan Stamenkovic, Srdan Skrbic, Carine Souveyet, Spyridon Vantolas, Giorgos Vasiliadis, Dejan Vukobratovic:
Cybersecurity for Industrial Internet of Things: Architecture, Models and Lessons Learned. IEEE Access 10: 124747-124765 (2022) - [j2]Abigail Goldsteen, Gilad Ezov, Ron Shmelkin, Micha Moffie, Ariel Farkash:
Data minimization for GDPR compliance in machine learning models. AI Ethics 2(3): 477-491 (2022) - [j1]Ehud Aharoni, Nir Drucker, Gilad Ezov, Hayim Shaul, Omri Soceanu:
Complex Encoded Tile Tensors: Accelerating Encrypted Analytics. IEEE Secur. Priv. 20(5): 35-43 (2022) - 2021
- [c1]Abigail Goldsteen, Gilad Ezov, Ron Shmelkin, Micha Moffie, Ariel Farkash:
Anonymizing Machine Learning Models. DPM/CBT@ESORICS 2021: 121-136 - 2020
- [i4]Abigail Goldsteen, Gilad Ezov, Ariel Farkash:
Reducing Risk of Model Inversion Using Privacy-Guided Training. CoRR abs/2006.15877 (2020) - [i3]Abigail Goldsteen, Gilad Ezov, Ron Shmelkin, Micha Moffie, Ariel Farkash:
Anonymizing Machine Learning Models. CoRR abs/2007.13086 (2020) - [i2]Abigail Goldsteen, Gilad Ezov, Ron Shmelkin, Micha Moffie, Ariel Farkash:
Data Minimization for GDPR Compliance in Machine Learning Models. CoRR abs/2008.04113 (2020) - [i1]Ehud Aharoni, Allon Adir, Moran Baruch, Gilad Ezov, Ariel Farkash, Lev Greenberg, Ramy Masalha, Dov Murik, Omri Soceanu:
Tile Tensors: A versatile data structure with descriptive shapes for homomorphic encryption. CoRR abs/2011.01805 (2020)
Coauthor Index
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