Neil Zhenqiang Gong

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Jan 08, 2021
Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, Mingwei Xu

* To appear in NDSS 2021

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Practical Blind Membership Inference Attack via Differential Comparisons

Jan 07, 2021
Bo Hui, Yuchen Yang, Haolin Yuan, Philippe Burlina, Neil Zhenqiang Gong, Yinzhi Cao

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FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Dec 27, 2020
Xiaoyu Cao, Minghong Fang, Jia Liu, Neil Zhenqiang Gong

* To appear in NDSS 2021

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Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

Dec 25, 2020
Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong

* Accepted by AAAI 2021

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Certified Robustness of Nearest Neighbors against Data Poisoning Attacks

Dec 07, 2020
Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong

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Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations

Nov 15, 2020
Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Hongbin Liu, Neil Zhenqiang Gong

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Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes

Oct 26, 2020
Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong

* Accepted by AsiaCCS'21

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* Accepted by WWW 2020; This is technical report version

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Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing

Feb 09, 2020
Jinyuan Jia, Binghui Wang, Xiaoyu Cao, Neil Zhenqiang Gong

* Accepted by WWW'20; This is technical report version

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Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing

Dec 20, 2019
Jinyuan Jia, Xiaoyu Cao, Binghui Wang, Neil Zhenqiang Gong

* ICLR 2020, code is available at this: https://github.com/jjy1994/Certify_Topk

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Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

Nov 26, 2019
Minghong Fang, Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong

* The paper was submitted to Usenix Security Symposium in February 2019 and will appear in Usenix Security Symposium 2020

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IPGuard: Protecting the Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary

Oct 30, 2019
Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong

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MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

Sep 26, 2019
Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, Neil Zhenqiang Gong

* To appear in CCS'19

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Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges

Sep 19, 2019
Jinyuan Jia, Neil Zhenqiang Gong

* Book chapter. arXiv admin note: substantial text overlap with arXiv:1805.04810

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Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation

Dec 06, 2018
Binghui Wang, Jinyuan Jia, Neil Zhenqiang Gong

* To appear in the 26th Annual Network and Distributed System Security Symposium (NDSS), Feb 2019

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Poisoning Attacks to Graph-Based Recommender Systems

Sep 11, 2018
Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, Jia Liu

* 34th Annual Computer Security Applications Conference (ACSAC), 2018; Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract appearing here is slightly shorter than that in the PDF file

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Neil Zhenqiang Gong

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Practical Blind Membership Inference Attack via Differential Comparisons

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

Certified Robustness of Nearest Neighbors against Data Poisoning Attacks

Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations

Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes

Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks

On the Intrinsic Differential Privacy of Bagging

Backdoor Attacks to Graph Neural Networks

Stealing Links from Graph Neural Networks

On Certifying Robustness against Backdoor Attacks via Randomized Smoothing

Influence Function based Data Poisoning Attacks to Top-N Recommender Systems

Certified Robustness of Community Detection against Adversarial Structural Perturbation via Randomized Smoothing

Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing

Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

IPGuard: Protecting the Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary

MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges

Graph-based Security and Privacy Analytics via Collective Classification with Joint Weight Learning and Propagation

Poisoning Attacks to Graph-Based Recommender Systems

AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning

Stealing Hyperparameters in Machine Learning

Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification