| Cheetah: Lean and fast secure {Two-Party} deep neural network inference Z Huang, W Lu, C Hong, J Ding 31st USENIX Security Symposium (USENIX Security 22), 809-826, 2022 | 143 | 2022 |
| Using fully homomorphic encryption for statistical analysis of categorical, ordinal and numerical data W Lu, S Kawasaki, J Sakuma Cryptology ePrint Archive, 2016 | 109 | 2016 |
| Privacy-preserving genome-wide association studies on cloud environment using fully homomorphic encryption WJ Lu, Y Yamada, J Sakuma BMC medical informatics and decision making 15, 1-8, 2015 | 86 | 2015 |
| PEGASUS: bridging polynomial and non-polynomial evaluations in homomorphic encryption W Lu, Z Huang, C Hong, Y Ma, H Qu 2021 IEEE Symposium on Security and Privacy (SP), 1057-1073, 2021 | 75 | 2021 |
| Covert security with public verifiability: Faster, leaner, and simpler C Hong, J Katz, V Kolesnikov, W Lu, X Wang Advances in Cryptology–EUROCRYPT 2019: 38th Annual International Conference …, 2019 | 37 | 2019 |
| Non-interactive and output expressive private comparison from homomorphic encryption W Lu, JJ Zhou, J Sakuma Proceedings of the 2018 on Asia Conference on Computer and Communications …, 2018 | 36 | 2018 |
| Efficient secure outsourcing of genome-wide association studies W Lu, Y Yamada, J Sakuma 2015 IEEE Security and Privacy Workshops, 3-6, 2015 | 34 | 2015 |
| Falcon: Fast spectral inference on encrypted data Q Lou, W Lu, C Hong, L Jiang Advances in Neural Information Processing Systems 33, 2364-2374, 2020 | 23 | 2020 |
| Homopai: A secure collaborative machine learning platform based on homomorphic encryption Q Li, Z Huang, W Lu, C Hong, H Qu, H He, W Zhang 2020 IEEE 36th International Conference on Data Engineering (ICDE), 1713-1717, 2020 | 21 | 2020 |
| More practical privacy-preserving machine learning as a service via efficient secure matrix multiplication W Lu, J Sakuma Proceedings of the 6th Workshop on Encrypted Computing & Applied Homomorphic …, 2018 | 20 | 2018 |
| Puma: Secure inference of llama-7b in five minutes Y Dong, W Lu, Y Zheng, H Wu, D Zhao, J Tan, Z Huang, C Hong, T Wei, ... arXiv preprint arXiv:2307.12533, 2023 | 14 | 2023 |
| Privacy-preserving collaborative machine learning on genomic data using TensorFlow C Hong, Z Huang, W Lu, H Qu, L Ma, M Dahl, J Mancuso Proceedings of the ACM Turing Celebration Conference-China, 39-44, 2020 | 13 | 2020 |
| Mpcvit: Searching for accurate and efficient mpc-friendly vision transformer with heterogeneous attention W Zeng, M Li, W Xiong, T Tong, W Lu, J Tan, R Wang, R Huang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 12 | 2023 |
| Ciphergpt: Secure two-party gpt inference X Hou, J Liu, J Li, Y Li, W Lu, C Hong, K Ren Cryptology ePrint Archive, 2023 | 11 | 2023 |
| Squirrel: A Scalable Secure {Two-Party} Computation Framework for Training Gradient Boosting Decision Tree W Lu, Z Huang, Q Zhang, Y Wang, C Hong 32nd USENIX Security Symposium (USENIX Security 23), 6435-6451, 2023 | 11 | 2023 |
| More efficient secure matrix multiplication for unbalanced recommender systems Z Huang, C Hong, C Weng, W Lu, H Qu IEEE Transactions on Dependable and Secure Computing 20 (1), 551-562, 2021 | 11 | 2021 |
| Faster secure multiparty computation of adaptive gradient descent W Lu, Y Fang, Z Huang, C Hong, C Chen, H Qu, Y Zhou, K Ren Proceedings of the 2020 Workshop on Privacy-Preserving Machine Learning in …, 2020 | 11 | 2020 |
| Bumblebee: Secure two-party inference framework for large transformers W Lu, Z Huang, Z Gu, J Li, J Liu, K Ren, C Hong, T Wei, WG Chen Cryptology ePrint Archive, 2023 | 5 | 2023 |
| Faster multiplication triplet generation from homomorphic encryption for practical privacy-preserving machine learning under a narrow bandwidth W Lu, J Sakuma Cryptology ePrint Archive, 2018 | 5 | 2018 |
| Secure similarity joins using fully homomorphic encryption MSH Cruz, T Amagasa, C Watanabe, W Lu, H Kitagawa Proceedings of the 19th International Conference on Information Integration …, 2017 | 5 | 2017 |
