| Local Model Poisoning Attacks to Byzantine-Robust Federated Learning M Fang, X Cao, J Jia, NZ Gong USENIX Security Symposium, 2020 | 1032 | 2020 |
| Stealing Hyperparameters in Machine Learning B Wang, NZ Gong IEEE Symposium on Security and Privacy, 2018 | 590 | 2018 |
| FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping X Cao, M Fang, J Liu, NZ Gong ISOC Network and Distributed System Security Symposium (NDSS), 2021 | 485 | 2021 |
| On the feasibility of internet-scale author identification A Narayanan, H Paskov, NZ Gong, J Bethencourt, E Stefanov, ECR Shin, ... IEEE Symposium on Security and Privacy, 2012 | 394 | 2012 |
| MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples J Jia, A Salem, M Backes, Y Zhang, NZ Gong ACM Conference on Computer and Communications Security (CCS), 2019 | 381 | 2019 |
| Joint link prediction and attribute inference using a social-attribute network NZ Gong, A Talwalkar, L Mackey, L Huang, ECR Shin, E Stefanov, ER Shi, ... ACM Transactions on Intelligent Systems and Technology (TIST) 5 (2), 27, 2014 | 323* | 2014 |
| Evolution of Social-Attribute Networks: Measurements, Modeling, and Implications using Google+ NZ Gong, W Xu, L Huang, P Mittal, E Stefanov, V Sekar, D Song ACM Internet Measurement Conference (IMC), 2012 | 267 | 2012 |
| Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification X Cao, NZ Gong Annual Computer Security Applications Conference (ACSAC), 2017 | 243 | 2017 |
| Poisoning Attacks to Graph-Based Recommender Systems M Fang, G Yang, NZ Gong, J Liu Annual Computer Security Applications Conference (ACSAC), 2018 | 227 | 2018 |
| SybilBelief: A Semi-supervised Learning Approach for Structure-based Sybil Detection NZ Gong, M Frank, P Mittal IEEE Transactions on Information Forensics and Security 9 (6), 2014 | 222 | 2014 |
| Backdoor Attacks to Graph Neural Networks Z Zhang, J Jia, B Wang, NZ Gong ACM Symposium on Access Control Models and Technologies (SACMAT), 2021 | 194 | 2021 |
| AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning J Jia, NZ Gong USENIX Security Symposium, 2018 | 185 | 2018 |
| You Are Who You Know and How You Behave: Attribute Inference Attacks via Users' Social Friends and Behaviors. NZ Gong, B Liu USENIX Security Symposium, 2016 | 168 | 2016 |
| FLCert: Provably Secure Federated Learning against Poisoning Attacks X Cao, Z Zhang, J Jia, NZ Gong IEEE Transactions on Information Forensics and Security, 2022 | 156* | 2022 |
| Influence function based data poisoning attacks to top-n recommender systems M Fang, NZ Gong, J Liu Proceedings of The Web Conference, 2020 | 155 | 2020 |
| Attacking Graph-based Classification via Manipulating the Graph Structure B Wang, NZ Gong ACM Conference on Computer and Communications Security (CCS), 2019 | 154 | 2019 |
| PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts K Zhu, J Wang, J Zhou, Z Wang, H Chen, Y Wang, L Yang, W Ye, ... arXiv preprint arXiv:2306.04528, 2023 | 146 | 2023 |
| Attribute inference attacks in online social networks NZ Gong, B Liu ACM Transactions on Privacy and Security (TOPS) 21 (1), 1-30, 2018 | 146 | 2018 |
| Badencoder: Backdoor attacks to pre-trained encoders in self-supervised learning J Jia, Y Liu, NZ Gong IEEE Symposium on Security and Privacy, 2022 | 145 | 2022 |
| Stealing Links from Graph Neural Networks X He, J Jia, M Backes, NZ Gong, Y Zhang USENIX Security Symposium, 2021 | 145 | 2021 |
Jinyuan JiaAssistant Professor, Penn State在 psu.edu 的电子邮件经过验证
