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Minghong Fang

Postdoctoral Associate

Minghong Fang

I'm a Postdoctoral Associate in the Department of Electrical and Computer Engineering at Duke University, working with Dr. Neil Gong. I obtained my Ph.D. degree from the Department of Electrical and Computer Engineering at The Ohio State University in August 2022, advised by Dr. Jia (Kevin) Liu. I am broadly interested in different areas of security, privacy, and machine learning.

I will join the Department of Computer Science and Engineering at University of Louisville as a tenure-track Assistant Professor in August 2024!

[Recruiting PhDs & Interns]: I am actively looking for highly motivated students for Ph.D. positions or research internships. Please email me with your CV and transcripts if you are interested.

Honors and Awards

  • IFIP/IEEE Networking Best Paper Runner-up Award, 2024.
  • USENIX Security Symposium’20 paper measured as one of the Normalized Top-100 Security Papers since 1981.
  • The Web Conference Student Travel Grant, 2021.
  • IEEE ICC Student Travel Grant, 2020.
  • Research Excellence Award, Iowa State University, 2020.
  • ACSAC Student Conferenceship Award, 2018.

Selected Publications [Full List]

  • Byzantine-Robust Decentralized Federated Learning. Created with Fabric.js 1.7.22 PDF

    Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia (Kevin) Liu, Songtao Lu, Yuchen Liu, and Neil Gong.

    In Proc. ACM CCS, 2024.

  • Poisoning Attacks on Federated Learning-based Wireless Traffic Prediction. Created with Fabric.js 1.7.22 PDF

    Zifan Zhang, Minghong Fang, Jiayuan Huang, and Yuchen Liu.

    In Proc. IFIP/IEEE Networking, 2024.

    Best Paper Runner-up Award

  • Robust Federated Learning Mitigates Client-side Training Data Distribution Inference Attacks. Created with Fabric.js 1.7.22 PDF

    Yichang Xu*, Ming Yin*, Minghong Fang, and Neil Zhenqiang Gong.

    In Proc. The Web Conference (WWW), 2024 (*co-primary authors).

    Yichang Xu and Ming Yin are undergraduate students mentored by me.

  • Poisoning Federated Recommender Systems with Fake Users. Created with Fabric.js 1.7.22 PDF

    Ming Yin*, Yichang Xu*, Minghong Fang, and Neil Zhenqiang Gong.

    In Proc. The Web Conference (WWW), 2024 (*co-primary authors).

    Ming Yin and Yichang Xu are undergraduate students mentored by me.

  • Data Poisoning Attacks and Defenses to Crowdsourcing Systems. Created with Fabric.js 1.7.22 PDF

    Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, and Jia Liu.

    In Proc. The Web Conference (WWW), 2021 (acceptance rate: 20.6%).

  • FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping. Created with Fabric.js 1.7.22 PDF Code

    Xiaoyu Cao*, Minghong Fang*, Jia Liu, and Neil Zhenqiang Gong.

    In Proc. NDSS, 2021 (*co-primary authors, acceptance rate: 15.2%).

  • Influence Function based Data Poisoning Attacks to Top-N Recommender Systems. Created with Fabric.js 1.7.22 PDF

    Minghong Fang, Neil Zhenqiang Gong, and Jia Liu.

    In Proc. The Web Conference (WWW), 2020 (acceptance rate: 25%).

  • Local Model Poisoning Attacks to Byzantine-Robust Federated Learning. Created with Fabric.js 1.7.22 PDF Code

    Minghong Fang*, Xiaoyu Cao*, Jinyuan Jia, and Neil Zhenqiang Gong.

    In Proc. USENIX Security Symposium, 2020 (*co-primary authors, acceptance rate: 16.1%).

    Measured as one of the Normalized Top-100 Security Papers since 1981.