Jinyuan Jia
Jinyuan Jia
Ph.D. student, Duke University
Verified email at duke.edu - Homepage
Cited by
Cited by
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning
M Fang, X Cao, J Jia, NZ Gong
USENIX Security Symposium, 2020
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
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning
J Jia, NZ Gong
USENIX Security Symposium, 2018
Random walk based fake account detection in online social networks
J Jia, B Wang, NZ Gong
IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2017
AttriInfer: Inferring user attributes in online social networks using markov random fields
J Jia, B Wang, L Zhang, NZ Gong
Proceedings of the WWW, 1561-1569, 2017
Structure-based sybil detection in social networks via local rule-based propagation
B Wang, J Jia, L Zhang, NZ Gong
IEEE Transactions on Network Science and Engineering (TNSE), 2019
Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing
J Jia, B Wang, X Cao, NZ Gong
The Web Conference (WWW), 2020
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing
J Jia, X Cao, B Wang, NZ Gong
International Conference on Learning Representations (ICLR), 2020
Backdoor attacks to graph neural networks
Z Zhang, J Jia, B Wang, NZ Gong
ACM Symposium on Access Control Models and Technologies (SACMAT), 2021
Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation
B Wang, J Jia, NZ Gong
ISOC Network and Distributed System Security Symposium (NDSS), 2019
On Certifying Robustness against Backdoor Attacks via Randomized Smoothing
B Wang, X Cao, J Jia, NZ Gong
CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision, 2020
Calibrate: Frequency Estimation and Heavy Hitter Identification with Local Differential Privacy via Incorporating Prior Knowledge
J Jia, NZ Gong
IEEE International Conference on Computer Communications (INFOCOM), 2019
Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks
J Jia, X Cao, NZ Gong
AAAI Conference on Artificial Intelligence (AAAI), 2021
Stealing Links from Graph Neural Networks
X He, J Jia, M Backes, NZ Gong, Y Zhang
USENIX Security Symposium, 2021
IPGuard: Protecting the Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary
X Cao, J Jia, NZ Gong
ACM ASIA Conference on Computer and Communications Security (ASIACCS), 2021
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges
J Jia, NZ Gong
Adaptive Autonomous Secure Cyber Systems, 23-40, 2020
Data Poisoning Attacks to Local Differential Privacy Protocols
X Cao, J Jia, NZ Gong
USENIX Security Symposium, 2021
Certified robustness of graph neural networks against adversarial structural perturbation
B Wang, J Jia, X Cao, NZ Gong
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Certified robustness of nearest neighbors against data poisoning attacks
J Jia, X Cao, NZ Gong
arXiv preprint arXiv:2012.03765, 2020
PointGuard: Provably Robust 3D Point Cloud Classification
H Liu, J Jia, NZ Gong
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
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