| Feature distillation: Dnn-oriented jpeg compression against adversarial examples Z Liu, Q Liu, T Liu, N Xu, X Lin, Y Wang, W Wen 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2019 | 256 | 2019 |
| CryptoGCN: fast and scalable homomorphically encrypted graph convolutional network inference R Ran, W Wang, Q Gang, J Yin, N Xu, W Wen Advances in Neural information processing systems 35, 37676-37689, 2022 | 14 | 2022 |
| Rrnet: Towards relu-reduced neural network for two-party computation based private inference H Peng, S Zhou, Y Luo, N Xu, S Duan, R Ran, J Zhao, S Huang, X Xie, ... arXiv preprint arXiv:2302.02292, 2023 | 10 | 2023 |
| Securing the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples N Xu, K Mahmood, H Fang, E Rathbun, C Ding, W Wen arXiv e-prints, arXiv: 2209.03358, 2022 | 9 | 2022 |
| Neurogenesis dynamics-inspired spiking neural network training acceleration S Huang, H Fang, K Mahmood, B Lei, N Xu, B Lei, Y Sun, D Xu, W Wen, ... 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 7 | 2023 |
| Analyzing and defending against membership inference attacks in natural language processing classification Y Wang, N Xu, S Huang, K Mahmood, D Guo, C Ding, W Wen, ... 2022 IEEE International Conference on Big Data (Big Data), 5823-5832, 2022 | 6 | 2022 |
| A system-level perspective to understand the vulnerability of deep learning systems T Liu, N Xu, Q Liu, Y Wang, W Wen Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019 | 5 | 2019 |
| NeuGuard: Lightweight neuron-guided defense against membership inference attacks N Xu, B Wang, R Ran, W Wen, P Venkitasubramaniam Proceedings of the 38th Annual Computer Security Applications Conference …, 2022 | 4 | 2022 |
| Polympcnet: Towards relu-free neural architecture search in two-party computation based private inference H Peng, S Zhou, Y Luo, S Duan, N Xu, R Ran, S Huang, C Wang, T Geng, ... arXiv preprint arXiv:2209.09424, 2022 | 4 | 2022 |
| Stealing your data from compressed machine learning models N Xu, Q Liu, T Liu, Z Liu, X Guo, W Wen 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 3 | 2020 |
| AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization Y Luo, N Xu, H Peng, C Wang, S Duan, K Mahmood, W Wen, C Ding, ... Proceedings of the 56th Annual IEEE/ACM International Symposium on …, 2023 | 2 | 2023 |
| Pasnet: Polynomial architecture search framework for two-party computation-based secure neural network deployment H Peng, S Zhou, Y Luo, N Xu, S Duan, R Ran, J Zhao, C Wang, T Geng, ... 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-6, 2023 | 2 | 2023 |
| Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering C Feng, N Xu, W Wen, P Venkitasubramaniam, C Ding 2023 IEEE Symposium on Security and Privacy (SP), 1944-1960, 2023 | 2 | 2023 |
| Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference R Ran, N Xu, T Liu, W Wang, G Quan, W Wen Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
| Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples N Xu, K Mahmood, H Fang, E Rathbun, C Ding, W Wen arXiv preprint arXiv:2209.03358, 2022 | | 2022 |
