Seulbae Kim
Pohang University of Science and Technology · 情報科学
研究室紹介
Professor Seulbae Kim's research lab specializes in ensuring the reliability, security, and correctness of complex software-intensive systems, with a strong focus on systems software, embedded systems, and cyber-physical systems. The lab investigates automated testing and vulnerability discovery techniques—particularly through protocol-aware fuzzing and symbolic execution—to detect deep-seated bugs in file systems, open-source software, autonomous driving systems, and IoT devices. A key research direction involves identifying semantic correctness bugs that arise from the interaction between software logic and physical constraints in robotics and smart home systems. The lab also pioneers scalable, unified approaches to system-level verification that bridge the gap between traditional testing and formal analysis.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15The ecosystem of open source software (OSS) has been growing considerably in size. In addition, code clones - code fragments that are copied and pasted within or between software systems - are also proliferating. Although code cloning may expedite the process of software development, it often critically affects the security of software because vulnerabilities and bugs can easily be propagated through code clones. These vulnerable code clones are increasing in conjunction with the growth of OSS,
File systems are too large to be bug free. Although handwritten test suites have been widely used to stress file systems, they can hardly keep up with the rapid increase in file system size and complexity, leading to new bugs being introduced and reported regularly. These bugs come in various flavors: simple buffer overflows to sophisticated semantic bugs. Although bug-specific checkers exist, they generally lack a way to explore file system states thoroughly. More importantly, no turnkey soluti
Autonomous driving has become real; semi-autonomous driving vehicles in an affordable price range are already on the streets, and major automotive vendors are actively developing full self-driving systems to deploy them in this decade. Before rolling the products out to the end-users, it is critical to test and ensure the safety of the autonomous driving systems, consisting of multiple layers intertwined in a complicated way. However, while safety-critical bugs may exist in any layer and even ac
Robotic systems are becoming an integral part of human lives. Responding to the increased demands for robot productions, Robot Operating System (ROS), an open-source middleware suite for robotic development, is gaining traction by providing practical tools and libraries for quickly developing robots. In this paper, we are concerned with a relatively less-tested class of bugs in ROS and ROS-based robotic systems, called semantic correctness bugs, including the violation of specification, violatio
Z-Wave smart home Internet of Things devices are used to save energy, increase comfort, and remotely monitor home activities. In the past, security researchers found Z-Wave device vulnerabilities through reverse engineering, manual audits, and penetration testing. However, they did not fully use fuzzing, which is an automated cost-effective testing technique. Thus, in this paper, we present VFUZZ, a protocol-aware blackbox fuzzing framework for quickly assessing vulnerabilities in Z-Wave devices
File systems are too large to be bug free. Although handwritten test suites have been widely used to stress file systems, they can hardly keep up with the rapid increase in file system size and complexity, leading to new bugs being introduced. These bugs come in various flavors: buffer overflows to complicated semantic bugs. Although bug-specific checkers exist, they generally lack a way to explore file system states thoroughly. More importantly, no turnkey solution exists that unifies the check
The usage and market size of video event data recorders (VEDRs), also known as car black boxes, are rapidly increasing. Since VEDRs can provide more visual information about car accident situations than any other device that is currently used for accident investigations (e.g., closed-circuit television), the integrity of the VEDR contents is important to any meaningful investigation. Researchers have focused on the file system integrity or photographic approaches to integrity verification. Howev
Open-source software (OSS) is widely reused as it provides convenience and efficiency in software development. Despite evident benefits, unmanaged OSS components can introduce threats, such as vulnerability propagation and license violation. Unfortunately, however, identifying reused OSS components is a challenge as the reused OSS is predominantly modified and nested. In this paper, we propose CENTRIS, a precise and scalable approach for identifying modified OSS reuse. By segmenting an OSS code
This is the artifact for the paper "Blind Spot in Sensor Fusion: Exploiting an Architectural Vulnerability to Hijack and Precisely Control UAVs" at Usenix VehicleSec '26
This is the artifact for the paper 'SwarmBox: A Plug-and-Play Drone Swarm Framework for Streamlined Development and Comprehensive Analysis' accepted at FSE 2026.
This is the artifact for the paper "Blind Spot in Sensor Fusion: Exploiting an Architectural Vulnerability to Hijack and Precisely Control UAVs" at Usenix VehicleSec '26
This is the artifact for the paper 'SwarmBox: A Plug-and-Play Drone Swarm Framework for Streamlined Development and Comprehensive Analysis' accepted at FSE 2026.
This is the full version of the paper published at ACM CCS 2022. This version includes the appendices (pages 14 and 15)
Unmanned Aerial Vehicles (UAVs), or drones, are emblematic examples of cyber-physical systems where computational components and physical processes integrate to enable autonomous navigation. UAVs rely heavily on sensors such as Inertial Measurement Units (IMU) and Global Positioning System (GPS) for accurate environmental awareness and control. However, the trust placed in these sensors makes UAVs vulnerable to adversarial attacks that compromise the UAV’s operational integrity. While prior work