Hi! Welcome to my homepage!

I am currently a postdoctoral researcher at Singapore Management University (SMU), hosted by Prof. Haiyang Xue. Before joining SMU, I worked as a cryptography researcher at Ant Group (2022-2024) and completed my PhD at the Institute of Software, Chinese Academy of Sciences (2016-2022), advised by Prof. Zhenfeng Zhang.

I am interested in threshold cryptography, zero-knowledge proofs, multi-party computation, and fully homomorphic encryption.

Experiences

  • Postdoctoral Researcher at Singapore Management University, 2024 - Now
  • Cryptography Researcher at Digital Technologies, Ant Group, 2022 - 2024
  • Ph.D in the Institute of Software, Chinese Academy of Sciences, 2016 - 2022

Publications

  • Robust Threshold ECDSA with Online-Friendly Design in Three Rounds
    • Guofeng Tang, Haiyang Xue
    • IEEE S&P 2025 [link]
  • Three-Round (Robust) Threshold ECDSA from Threshold CL Encryption
    • Bowen Jiang, Guofeng Tang, Haiyang Xue
    • ACISP 2025
  • Batch Range Proof: How to Make Threshold ECDSA More Efficient
    • Guofeng Tang, Shuai Han, Li Lin, Changzheng Wei, Ying Yan
    • ACM CCS 2024 [eprint]
  • Rhombus: Fast Homomorphic Matrix-Vector Multiplication for Secure Two-Party Inference
    • Jiaxing He, Kang Yang, Guofeng Tang, Zhangjie Huang, Li Lin, Changzheng Wei, Ying Yan
    • ACM CCS 2024 [eprint]
  • Efficient Lattice-Based Threshold Signatures with Functional Interchangeability
    • Guofeng Tang, Bo Pang, Long Chen, Zhenfeng Zhang
    • IEEE Transactions on Information Forensics and Security - TIFS, 2023 [eprint]
  • On Tightly-Secure (Linkable) Ring Signatures
    • Guofeng Tang
    • ICICS 2021 [link]
  • Lattice HIBE with Faster Trapdoor Delegation and Applications
    • Guofeng Tang, Tian Qiu
    • ICICS 2020 [link]

Research Competition

  • iDASH 2023 Secure Genome Analysis Competition
    • First Place of Track 1: Secure Relative Detection in (Forensic) Database
  • iDASH 2022 Secure Genome Analysis Competition
    • Third Place of Track 2: Secure Model Evaluation on Homomorphically Encrypted Genotype Data