SymbFuzz: Symbolic Execution Guided Hardware Fuzzing
Symbolic execution guided hardware fuzzing for deeper vulnerability detection in hardware designs.
🔐(he/him)
Senior SoC Architect & Hardware Security Expert
Ph.D. in Electrical Engineering
KU Leuven, imec-COSIC (Belgium)
M.Sc. in Information Security and Applied Cryptographic Engineering
Korea University (South Korea)
My research bridges the gap between theoretical cryptography and silicon-level implementation, with a focus on building verifiably secure hardware systems for the post-quantum era.
Current research areas:
Symbolic execution guided hardware fuzzing for deeper vulnerability detection in hardware designs.
Fuzzing-based verification framework for Network-on-Chip security and functional validation.
ML-powered bidirectional DShot protocol with FPGA-based neural network for real-time ESC timing correction.
Three-phase DyCML design for balanced power consumption and enhanced side-channel resistance. **Best Paper Award.**
A comprehensive look at how modern SoCs build trust from the first instruction — Boot ROM, Secure Boot, Measured Boot, and Trusted Execution Environments.
Software security isn't enough for UAVs. Drones need hardware-level protection against GPS spoofing, firmware tampering, and communication hijacking.
Korea's cryptographic module validation program is evolving for the post-quantum era. Here's what semiconductor companies need to know and prepare.
Mathematically secure doesn't mean implementation-secure. Lattice-based PQC is vulnerable to power analysis and EM attacks — and only hardware can fix it.
Software-only PQC migration falls short in embedded systems. Here's why quantum-resistant security must be built at the silicon level.