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S3 Lab - Software & Systems Security Laboratory
South Engineering and Computer Science Building

about us

We conduct research and build practical tools to analyze the security of diverse software and develop dependable systems using program analysis, operating systems and cyber-physical systems techniques.

If you are interested in working with us, please look at this page.

S3 Lab is part of the Cyber Security Research and Education Institute and the Department of Computer Science at the University of Texas at Dallas.

recent news (see more)

A new grant is awarded from the UT Dallas SPIRe program. Thanks ORI for support!
Chung Hwan Kim is a program committee member of DSN 2025.
Md Shihabul Islam successfully defended his Ph.D. dissertation. Congratulations!
Chung Hwan Kim is a program committee member of SafeThings 2024.

highlighted projects (see more)

AutoInsight AutoInsight

The AutoInsight project applies advanced techniques in software security and control systems to build a new security analysis platform for autonomous driving systems.

RetroV RetroV

Robotic vehicles (as known as drones) are facing various threats of cyber-physical attacks that exploit their security vulnerabilities. RetroV develops automated analysis tools to find such vulnerabilities in existing robotic vehicle systems retrospectively and retrofits their design against advanced cyber-physical attacks.

AI Vault AI Vault

The AI Vault project designs and develops a new trusted execution environment tailored to run artificial intelligence and machine learning programs on modern AI platforms (e.g., cloud and embedded devices) while providing strong data confidentiality and high efficiency.

Shear Shear

The Shear project creates a secure environment for the least-authority execution of over-privileged applications that may be exploited by adversaries to launch privileged attacks.


The CLUE project develops an infrastructure to detect and diagnose system anomalies in enterprise and cloud systems. These anomalies include stealthy malware and other types of hidden system anomalies. CLUE provides a diverse set of tools to find and understand such anomalies with minimal disruption to the target system.

research areas

courses and seminar (see more)

recent publications (see more)

FreePart: Hardening Data Processing Software via Framework-based Partitioning and Isolation
Ali Ahmad, Gang Wang, Chung Hwan Kim, Suman Jana, Zhiqiang Lin, and Yonghwi Kwon
In ASPLOS 2024 [ pdf :: bibtex ]
Poster: Deterministic Replay and Debugging for Robotic Systems
Md Nazmus Sakib, Seungmok Kim, Zelun Kong, Seulbae Kim, Kyu Hyung Lee, Heejo Lee, and Chung Hwan Kim
In ACSAC 2023 [ pdf :: bibtex ]
Building GPU TEEs using CPU Secure Enclaves with GEVisor
Xiaolong Wu, Dave (Jing) Tian, and Chung Hwan Kim
In SOCC 2023 [ pdf :: slides :: bibtex ]
DriveFuzz: Discovering Autonomous Driving Bugs through Driving Quality-Guided Fuzzing
Seulbae Kim, Major Liu, Junghwan Rhee, Yuseok Jeon, Yonghwi Kwon, and Chung Hwan Kim
In CCS 2022 [ pdf :: slides :: bibtex ]