Heedong Yang

Heedong Yang

| 양 희 동

Ph.D Student, Computer Science and Engineering, Korea University

I am a Ph.D. candidate in Computer Science and Engineering at Korea University, under Professor Seunghoon Woo at the SSP Lab. My research interests are binary analysis and software security. I focus on binary analysis, not just for C/C++ but across a broader range of languages, to help secure the software supply chain.

Previously, I worked as a researcher at the KAIST CSRC(Cyber Security Research Center, KAIST), where I focused on binary analysis. I received my M.S. and B.S. in Computer Engineering from HPSC lab, Hannam University

Research Experience

  • •
    SSP Lab, Korea University

    Student Researcher · Seoul, South Korea · 2024.03 ~ Present

  • •
    SSLab, Georgia Institute of Technology

    Visiting Scholar · Atlanta, GA, USA · 2026.05

  • •
    Cyber Security Research Center, KAIST

    Researcher / Binary Analysis Team · Daejeon, South Korea · 2022.03 ~ 2024.02

  • •
    Fukuoka Institute of Technology

    Research Trainee (VIA'19W) · Fukuoka, Japan · 2019.02

  • •
    HPSC Lab, Hannam University

    Student Researcher · Daejeon, South Korea · 2018.06 ~ 2022.02

Research Interest

Binary Analysis
Software Security
Software Supply Chain Security

Talks & Presentations

Awards & Honors

  • 1.
    CISC-W'21 Best Paper Award

    Nov. 2021 · South Korea

  • 2.
    SMA-2020 Best Paper Award (Bronze)

    Sep. 2020 · South Korea

  • 3.
    CISC-S'20 Best Paper Award

    Jun. 2020 · South Korea

  • 4.
    KIISC-CC'19 Best Paper Award

    Sep. 2019 · South Korea

Open-Source Software Project

  • 1.
    SBridge

    Developer · F# · 2026

    A source to binary function matching tool for binary analysis (Paper Artifact)

  • 2.
    B2R2

    Main Contributor · F# · 2022 ~ 2023

    An open-source tool for binary analysis

  • 3.
    KOALA (KAIST Open-source Anonymization Platform)

    Main Contributor · Java · 2023

    A platform for data anonymization balancing privacy protection with data utility using ARX framework

Patents

  • 1.
    Privacy Model Recommendation and De-identification Method for Preventing Privacy Breach and System Performing the Same

    Application (10-2023-0113310) · South Korea · 2023

International Conference

International Journal

Domestic Journal(Kor)

Contact

Seoul, South Korea

heedongy[at]korea.ac.kr

BibTeX