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S2Lab (Secure Software Lab) is a lab dedicated to software and systems security problems. In particular, our research focus is designing and implementing advanced bug sanitization and mitigation techniques to protect operating systems and user applications in existing and emerging areas (e.g., autonomous driving, drones) by leveraging compiler-based, fuzzing, and AI technologies.
Major research field
Software security, System Security
Desired field of research
RUST security, Container security, Autonomous driving security, AI-based security
Research Keywords and Topics
Software security, System Security, RUST security, Container security, Autonomous driving security, AI-based security
Research Publications
IEEE Symposium on Security and Privacy, SwarmFlawFinder: Discovering and Exploiting Logic Flaws of Swarm Algorithms, Chijung Jung, Ali Ahad, Yuseok Jeon, Yonghwi Kwon, 2022
USENIX Annual Technical Conference, FuZZan: Efficient Sanitizer Metadata Design for Fuzzing, Yuseok Jeon, Wookhyun Han, Nathan
Burow, Mathis Payer, 2020
ACM Conference on Computer and Communications Security, HexType: Efficient Detection of Type Confusion Errors for C++, Yuseok Jeon, Priyam Biswas, Scott Carr, Byoungyoung Lee, Mathias Payer, 2017
Patents
Fine-grained analysis and prevention of invalid privilege transitions, Junghwan Rhee, Yuseok Jeon, Zhichun Li, Kangkook Jee, Zhenyu Wu, Guofei Jiang, 2019
Blackbox Program Privilege Flow Analysis with Inferred Program Behavior Context, Junghwan Rhee, Yuseok Jeon, Zhichun Li, Kangkook Jee, Zhenyu Wu, Guofei Jiang, 2019
국가과학기술표준분류
- EE. 정보/통신
- EE03. 정보보호
- EE0301. 공통 보안기술
국가기술지도분류
- 정보-지식-지능화 사회 구현
- 011700. 정보보호기술
녹색기술분류
- 녹색기술관련 과제 아님
- 녹색기술관련 과제 아님
- 999. 녹색기술 관련과제 아님
6T분류
- IT 분야
- 정보처리 시스템 및 S/W
- 010313. 전자상거래 기술