Ruofan Liu

Ruofan Liu

Research Fellow@National University of Singapore

Ruofan Liu's Personal Website

👋 Welcome to Liu Ruofan, 刘若凡's Homepage

📚 Education

  • 2024.10 - Present. Research Fellow in Computer Science, National University of Singapore (NUS). Research Interest: AI for Web Security.
  • 2021.01 - 2024.10. Ph.D. in Computer Science, National University of Singapore (NUS). Supervisor: Prof. Dong Jin Song.
  • 2016.08 - 2020.06. B.S. in Statistics, National University of Singapore (NUS). FYP Supervisor: Prof. Alexandre Thiéry.

🔥 News

  • 2025.03: 🎉🎉 Our paper "GUIPilot: A Consistency-based Mobile GUI Testing Approach for Detecting Application-specific Bugs" is accepted by ISSTA'25 (acceptance rate: 19%)

📝 Selected Publications

  • USENIX Security 2024
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    Ruofan Liu, Yun Lin, Xiwen Teoh, Gongshen Liu, Zhiyong Huang, and Jin Song Dong.
    Less Defined Knowledge and More True Alarms: Reference-based Phishing Detection without a Pre-defined Reference List.
    [Paper] [Code] [Video]

  • USENIX Security 2024
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    Xiwen Teoh, Yun Lin, Ruofan Liu, Zhiyong Huang and Jin Song Dong.
    PhishDecloaker: Detecting CAPTCHA-cloaked Phishing Websites via Hybrid Vision-based Interactive Models.
    [Paper] [Code] [Video]

  • USENIX Security 2023
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    Ruofan Liu, Yun Lin, Yifan Zhang, Penn Han Lee, and Jin Song Dong.
    Knowledge Expansion and Counterfactual Interaction for Reference-Based Phishing Detection.
    [Paper] [Code] [Video]

  • USENIX Security 2022
  • Thumbnail
    Ruofan Liu, Yun Lin, Xianglin Yang, Siang Hwee Ng, Dinil Mon Divakaran, Jin Song Dong.
    Inferring Phishing Intention via Webpage Appearance and Dynamics: A Deep Vision Based Approach.
    [Paper] [Code] [Video]

  • USENIX Security 2021
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    Yun Lin#, Ruofan Liu#, Dinil Mon Divakaran, Jun Yang Ng, Qing Zhou Chan, Yiwen Lu, Yuxuan Si, Fan Zhang, Jin Song Dong.
    Phishpedia: A Hybrid Deep Learning Based Approach to Visually Identify Phishing Webpages.
    [Paper] [Code] [Video]

⚒️ Tools and Systems

  • Phishpedia: 1st referenced-based phishing website detector.
  • PhishIntention: Reference-based phishing detector with both the brand intention and credential-taking intention.
  • DynaPhish: A complementary module for all reference-based phishing detectors with brand knowledge expansion and counterfactual interaction.
  • PhishLLM: A LLM-empowered phishing detector.
  • Influence4Metric: An influence-function-based explanation and debugging tool for Deep Metric Learning Tasks.

🏆 Awards

  • 2024. China International College Students’ Innovation Competition 2024 Bronze Medal
    中国国际大学生创新大赛（2024）高教主赛道国际项目全国铜奖（全国前0.04%）
  • 2024. China International College Students’ Innovation Competition 2024 (Shanghai) Silver Medal
    中国国际大学生创新大赛（2024）高教主赛道国际项目（上海赛区）专项赛银奖
  • 2024. National University of Singapore Dean's Graduate Research Excellence Award
  • 2021. National University of Singapore Research Achievement Award in 2021/2022 Sem 1
  • 2020. Top 1 student in NUS Statistics Batch 2020
  • 2020. Lijen Industrial Development Medal (Best Academic Exercise/Projects in the Discipline) in Academic Year 2019
  • 2020. NTUC Medal in Academic Year 2019
  • 2020. Saw Swee Hock Gold Medal in the Academic Year 2019
  • 2020. SNAS Award 2020 (Singapore National Academy of Science)

    • 🏷 Patent

  • 2020. Yun Lin, Ruofan Liu, Dinil Mon Divakaran, Jun Yang Ng, and Jin Song Dong. Phishpedia: Towards an Approach of Phishing Identification with Visual Explanation. Provisional patent filed in Singapore (Trustwave, Singtel). NO. 10202011155P

    • 💪 Service

  • 2024. Reviewer for the Transactions on Information Forensics & Security
  • 2023. Reviewer for the 28th IEEE Pacific Rim International Symposium on Dependable Computing

    • 📞 Contacts

    Email: liu.ruofan16[at]u[dot]nus[dot]edu

    GitHub page: https://github.com/lindsey98/

    Google Scholar: https://scholar.google.com/citations?user=g2M2UwsAAAAJ&hl=en