VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery. - Seulbae Kim; Seunghoon Woo; Heejo Lee; Hakjoo Oh (IEEE Symposium on Security and Privacy, 2017)

Software systems at risk: An empirical study of cloned vulnerabilities in practice. - Seulbae Kim; Heejo Lee (Comput. Secur., 2018)

Finding semantic bugs in file systems with an extensible fuzzing framework. - Seulbae Kim; Meng Xu 001; Sanidhya Kashyap; Jungyeon Yoon; Wen Xu 002; Taesoo Kim (SOSP, 2019)

Finding Bugs in File Systems with an Extensible Fuzzing Framework. - Seulbae Kim; Meng Xu 001; Sanidhya Kashyap; Jungyeon Yoon; Wen Xu 002; Taesoo Kim (ACM Trans. Storage, 2020)

Centris: A Precise and Scalable Approach for Identifying Modified Open-Source Software Reuse. - Seunghoon Woo; Sunghan Park; Seulbae Kim; Heejo Lee; Hakjoo Oh (ICSE, 2021)

DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing. - Seulbae Kim; Major Liu; Junghwan John Rhee; Yuseok Jeon; Yonghwi Kwon 001; Chung Hwan Kim (CCS, 2022)

RoboFuzz: fuzzing robotic systems over robot operating system (ROS) for finding correctness bugs. - Seulbae Kim; Taesoo Kim (ESEC/SIGSOFT FSE, 2022)

Riding the IoT Wave With VFuzz: Discovering Security Flaws in Smart Homes. - Carlos Nkuba Kayembe; Seulbae Kim; Sven Dietrich; Heejo Lee (IEEE Access, 2022)

Fortifying Cyber-Physical Systems through Comprehensive Bug-finding and Mitigation. - Seulbae Kim (2024)

SoundBoost: Effective RCA and Attack Detection for UAV via Acoustic Side-Channel. - Haoran Wang; Zheng Yang; Sangdon Park; Yibin Yang 001; Seulbae Kim; Willian T. Lunardi; Martin Andreoni; Taesoo Kim; Wenke Lee (DSN, 2025)