| Model Inversion Attacks Against Collaborative Inference Z He, T Zhang, RB Lee Annual Computer Security Applications Conference (ACSAC), 148-162, 2019 | 357 | 2019 |
| Machine learning based ddos attack detection from source side in cloud Z He, T Zhang, RB Lee IEEE International Conference on Cyber Security and Cloud Computing (CSCloud …, 2017 | 218 | 2017 |
| How secure is your cache against side-channel attacks? Z He, RB Lee IEEE/ACM International Symposium on Microarchitecture (MICRO), 341-353, 2017 | 109 | 2017 |
| Attacking and Protecting Data Privacy in Edge–Cloud Collaborative Inference Systems Z He, T Zhang, RB Lee IEEE Internet of Things Journal 8 (12), 9706-9716, 2020 | 108 | 2020 |
| Privacy-preserving Machine Learning through Data Obfuscation T Zhang, Z He, RB Lee arXiv preprint arXiv:1807.01860, 2018 | 105 | 2018 |
| Sensitive-sample fingerprinting of deep neural networks Z He, T Zhang, R Lee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 99 | 2019 |
| ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces Z He, S Sunkara, X Zang, Y Xu, L Liu, N Wichers, G Schubiner, R Lee, ... AAAI Conference on Artificial Intelligence (AAAI), 2021 | 81 | 2021 |
| Movie Gen: A Cast of Media Foundation Models A Polyak, A Zohar, A Brown, A Tjandra, A Sinha, A Lee, A Vyas, B Shi, ... arXiv preprint arXiv:2410.13720, 2024 | 77 | 2024 |
| Miss the Point: Targeted Adversarial Attack on Multiple Landmark Detection Q Yao, Z He, H Han, SK Zhou International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 43 | 2020 |
| Power-grid controller anomaly detection with enhanced temporal deep learning Z He, A Raghavan, G Hu, S Chai, R Lee IEEE International Conference On Trust, Security And Privacy In Computing …, 2019 | 38* | 2019 |
| Verideep: Verifying integrity of deep neural networks through sensitive-sample fingerprinting Z He, T Zhang, RB Lee arXiv preprint arXiv:1808.03277, 2018 | 34 | 2018 |
| Trainable Projected Gradient Method for Robust Fine-tuning J Tian, Z He, X Dai, CY Ma, YC Liu, Z Kira Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 33 | 2023 |
| New Models for Understanding and Reasoning about Speculative Execution Attacks Z He, G Hu, R Lee IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2021 | 30 | 2021 |
| A hierarchical feature constraint to camouflage medical adversarial attacks Q Yao, Z He, Y Lin, K Ma, Y Zheng, SK Zhou Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 24 | 2021 |
| SoK: Hardware Defenses Against Speculative Execution Attacks G Hu, Z He, RB Lee 2021 International Symposium on Secure and Private Execution Environment …, 2021 | 23 | 2021 |
| Cloudshield: Real-time anomaly detection in the cloud Z He, G Hu, RB Lee Proceedings of the Thirteenth ACM Conference on Data and Application …, 2023 | 8 | 2023 |
| Smartphone Impostor Detection with Behavioral Data Privacy and Minimalist Hardware Support G Hu, Z He, RB Lee TinyML Research Symposium, 2021 | 8* | 2021 |
| Imagine yourself: Tuning-Free Personalized Image Generation Z He, B Sun, F Juefei-Xu, H Ma, A Ramchandani, V Cheung, S Shah, ... arXiv preprint arXiv:2409.13346, 2024 | 6 | 2024 |
| Adversarial Medical Image with Hierarchical Feature Hiding Q Yao, Z He, Y Li, Y Lin, K Ma, Y Zheng, SK Zhou IEEE Transactions on Medical Imaging, 2023 | 4 | 2023 |
| Medical Aegis: Robust adversarial protectors for medical images Q Yao, Z He, SK Zhou arXiv preprint arXiv:2111.10969, 2021 | 4 | 2021 |
