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Neil Zhenqiang Gong

Neil Zhenqiang Gong

D-Index & Metrics

Computer Science

D-Index
50
Citations
8969
World Ranking
5665
National Ranking
2578

Overview

Neil Zhenqiang Gong is affiliated with Duke University in the United States. Their research primarily falls within the field of Computer Science, with a substantial focus on Artificial Intelligence. Additional subfields include Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Computer Networks and Communications.

Their academic work spans several main topics, notably Adversarial Robustness in Machine Learning, Privacy-Preserving Technologies in Data, Advanced Graph Neural Networks, Anomaly Detection Techniques and Applications, Digital Media Forensic Detection, Cryptography and Data Security, and Advanced Steganography and Watermarking Techniques.

Neil Zhenqiang Gong has published extensively in various venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security
  • Proceedings on Privacy Enhancing Technologies
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Some of their recent papers are:

  • FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients, 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Provably Secure Federated Learning against Malicious Clients, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning, 2022, 2022 IEEE Symposium on Security and Privacy (SP)
  • Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • FLCert: Provably Secure Federated Learning Against Poisoning Attacks, 2022, IEEE Transactions on Information Forensics and Security

Frequent coauthors working with Neil Zhenqiang Gong include:

  • Jinyuan Jia
  • Xiaoyu Cao
  • Minghong Fang
  • Yuepeng Hu

The research contributions cover topics that include theoretical and practical aspects of federated learning security and robustness against model poisoning and backdoor attacks, as well as certifiable defenses in machine learning systems.

Best Publications

  • FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.

    Xiaoyu Cao;Minghong Fang;Jia Liu;Neil Zhenqiang Gong

  • Stealing Hyperparameters in Machine Learning

    Binghui Wang;Neil Zhenqiang Gong

  • On the Feasibility of Internet-Scale Author Identification

    A. Narayanan;H. Paskov;N. Z. Gong;J. Bethencourt

  • Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

    Minghong Fang;Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

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

    Jinyuan Jia;Ahmed Salem;Michael Backes;Yang Zhang

  • FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients

    Unknown

  • Evolution of social-attribute networks: measurements, modeling, and implications using google+

    Neil Zhenqiang Gong;Wenchang Xu;Ling Huang;Prateek Mittal

  • SybilBelief: A Semi-Supervised Learning Approach for Structure-Based Sybil Detection

    Neil Zhenqiang Gong;Mario Frank;Prateek Mittal

  • Joint Link Prediction and Attribute Inference Using a Social-Attribute Network

    Neil Zhenqiang Gong;Ameet Talwalkar;Lester Mackey;Ling Huang

  • Backdoor Attacks to Graph Neural Networks

    Zaixi Zhang;Jinyuan Jia;Binghui Wang;Neil Zhenqiang Gong

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

    Xiaoyu Cao;Neil Zhenqiang Gong

  • PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

    Unknown

  • TrustLLM: Trustworthiness in Large Language Models

    Unknown

  • Local Model Poisoning Attacks to Byzantine-Robust Federated Learning.

    Minghong Fang;Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

  • Attacking Graph-based Classification via Manipulating the Graph Structure

    Binghui Wang;Neil Zhenqiang Gong

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

    Minghong Fang;Neil Zhenqiang Gong;Jia Liu

  • Random Walk Based Fake Account Detection in Online Social Networks

    Jinyuan Jia;Binghui Wang;Neil Zhenqiang Gong

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

    Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

  • Personalized Mobile App Recommendation: Reconciling App Functionality and User Privacy Preference

    Bin Liu;Deguang Kong;Lei Cen;Neil Zhenqiang Gong

  • Attribute Inference Attacks in Online Social Networks

    Neil Zhenqiang Gong;Bin Liu

  • Poisoning Attacks to Graph-Based Recommender Systems

    Minghong Fang;Guolei Yang;Neil Zhenqiang Gong;Jia Liu

  • Poisoning Attacks to Graph-Based Recommender Systems

    Minghong Fang;Guolei Yang;Neil Zhenqiang Gong;Jia Liu

  • Fake Co-visitation Injection Attacks to Recommender Systems.

    Guolei Yang;Neil Zhenqiang Gong;Ying Cai

  • Practical Blind Membership Inference Attack via Differential Comparisons

    Bo Hui;Yuchen Yang;Haolin Yuan;Philippe Burlina

  • On Certifying Robustness against Backdoor Attacks via Randomized Smoothing

    Binghui Wang;Xiaoyu Cao;Jinyuan jia;Neil Zhenqiang Gong

  • Data Poisoning Attacks to Deep Learning Based Recommender Systems.

    Hai Huang;Jiaming Mu;Neil Zhenqiang Gong;Qi Li

Frequent Co-Authors

Dawn Song
Dawn Song University of California, Berkeley
Prateek Mittal
Prateek Mittal Princeton University
Hongxia Jin
Hongxia Jin Samsung (United States)
Ling Huang
Ling Huang Intel (United States)
Mathias Payer
Mathias Payer École Polytechnique Fédérale de Lausanne
Michael Backes
Michael Backes University of Oxford
Sanjeev R. Kulkarni
Sanjeev R. Kulkarni Princeton University
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Jingren Zhou
Jingren Zhou Alibaba Group (China)
Defu Lian
Defu Lian University of Science and Technology of China

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