A little is enough: Circumventing defenses for distributed learning M Baruch, G Baruch, Y Goldberg Advances in Neural Information Processing Systems, 8632-8642, 2019 | 406 | 2019 |
Deceiving end-to-end deep learning malware detectors using adversarial examples F Kreuk, A Barak, S Aviv-Reuven, M Baruch, B Pinkas, J Keshet NeurIPS Workshop on Security in Machine Learning, 2018 | 171* | 2018 |
HeLayers: a tile tensors framework for large neural networks on encrypted data. PoPETs (2023) E Aharoni, A Adir, M Baruch, N Drucker, G Ezov, A Farkash, L Greenberg, ... | 48* | 2023 |
Domain generation algorithm detection using machine learning methods M Baruch, G David Cyber security: power and technology, 133-161, 2018 | 14* | 2018 |
A methodology for training homomorphic encryption friendly neural networks M Baruch, N Drucker, L Greenberg, G Moshkowich International Conference on Applied Cryptography and Network Security, 536-553, 2022 | 12* | 2022 |
He-pex: Efficient machine learning under homomorphic encryption using pruning, permutation and expansion E Aharoni, M Baruch, P Bose, A Buyuktosunoglu, N Drucker, S Pal, ... arXiv preprint arXiv:2207.03384, 2022 | 8 | 2022 |
HeLayers: a tile tensors framework for large neural networks on encrypted data. CoRR abs/2011.0 (2020) E Aharoni, A Adir, M Baruch, N Drucker, G Ezov, A Farkash, L Greenberg, ... arXiv preprint arXiv:2011.01805, 2020 | 6 | 2020 |
Sensitive tuning of large scale CNNs for E2E secure prediction using homomorphic encryption M Baruch, N Drucker, G Ezov, E Kushnir, J Lerner, O Soceanu, ... arXiv preprint arXiv:2304.14836, 2023 | 5 | 2023 |
Tile tensors: A versatile data structure with descriptive shapes for homomorphic encryption E Aharoni, A Adir, M Baruch, G Ezov, A Farkash, L Greenberg, R Masalha, ... CoRR, abs/2011.01805, 2020 | 4 | 2020 |
Poster: Secure SqueezeNet inference in 4 minutes E Aharoni, M Baruch, N Drucker, G Ezov, E Kushnir, G Moshkowich, ... 43rd IEEE Symposium on Security and Privacy (2022). Read more, 2022 | 3 | 2022 |
Converting Transformers to Polynomial Form for Secure Inference Over Homomorphic Encryption I Zimerman, M Baruch, N Drucker, G Ezov, O Soceanu, L Wolf arXiv preprint arXiv:2311.08610, 2023 | 2 | 2023 |
Hebrew psychological lexicons N Shapira, D Atzil-Slonim, D Juravski, M Baruch, D Stolowicz-Melman, ... Proceedings of the Seventh Workshop on Computational Linguistics and …, 2021 | 2 | 2021 |
Prune, permute and expand: efficient machine learning under non-client-aided homomorphic encryption E Aharoni, M Baruch, P Bose, A Buyuktosunoglu, N Drucker, S Pal, ... Annual IEEE/ACM International Symposium on Microarchitecture, 2022 | 1 | 2022 |
Packing machine learning models using pruning and permutation PAL Subhankar, A Buyuktosunoglu, E Aharoni, N Drucker, O Soceanu, ... US Patent App. 17/857,593, 2024 | | 2024 |
Machine learning network extension based on homomorphic encryption packings N Drucker, M Baruch US Patent App. 17/838,901, 2023 | | 2023 |
Efficient Pruning for Machine Learning Under Homomorphic Encryption E Aharoni, M Baruch, P Bose, A Buyuktosunoglu, N Drucker, S Pal, ... European Symposium on Research in Computer Security, 204-225, 2023 | | 2023 |