Seuraa
Neil Zhenqiang Gong
Neil Zhenqiang Gong
Assistant Professor, Duke University
Vahvistettu sähköpostiosoite verkkotunnuksessa duke.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning
M Fang, X Cao, J Jia, NZ Gong
USENIX Security Symposium, 2020
10122020
Stealing Hyperparameters in Machine Learning
B Wang, NZ Gong
IEEE Symposium on Security and Privacy, 2018
5882018
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
4672021
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
3962012
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
3752019
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
324*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
2682012
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification
X Cao, NZ Gong
Annual Computer Security Applications Conference (ACSAC), 2017
2402017
Poisoning Attacks to Graph-Based Recommender Systems
M Fang, G Yang, NZ Gong, J Liu
Annual Computer Security Applications Conference (ACSAC), 2018
2232018
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
2212014
Backdoor Attacks to Graph Neural Networks
Z Zhang, J Jia, B Wang, NZ Gong
ACM Symposium on Access Control Models and Technologies (SACMAT), 2021
1902021
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning
J Jia, NZ Gong
USENIX Security Symposium, 2018
1832018
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
1662016
FLCert: Provably Secure Federated Learning against Poisoning Attacks
X Cao, Z Zhang, J Jia, NZ Gong
IEEE Transactions on Information Forensics and Security, 2022
154*2022
Influence function based data poisoning attacks to top-n recommender systems
M Fang, NZ Gong, J Liu
Proceedings of The Web Conference, 2020
1542020
Attacking Graph-based Classification via Manipulating the Graph Structure
B Wang, NZ Gong
ACM Conference on Computer and Communications Security (CCS), 2019
1502019
Badencoder: Backdoor attacks to pre-trained encoders in self-supervised learning
J Jia, Y Liu, NZ Gong
IEEE Symposium on Security and Privacy, 2022
1452022
Attribute inference attacks in online social networks
NZ Gong, B Liu
ACM Transactions on Privacy and Security (TOPS) 21 (1), 1-30, 2018
1452018
On Your Social Network De-anonymizablity: Quantification and Large Scale Evaluation with Seed Knowledge
S Ji, W Li, NZ Gong, P Mittal, R Beyah
ISOC Network and Distributed System Security Symposium (NDSS), 2015
142*2015
Stealing Links from Graph Neural Networks
X He, J Jia, M Backes, NZ Gong, Y Zhang
USENIX Security Symposium, 2021
1412021
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Artikkelit 1–20