STEM, Research, The University of Hong Kong, Leadership & Research Laidlaw Scholars, Laidlaw Conference 2025
Fuzzing with Hopper++: Applying LLM to Program Generation and Software Security
The focus of this research is to leverage the power of Generative AI and apply Large Language Model to fuzz testing. Based on the previous interpretative fuzzing project Hopper, this work introduces Hopper++, an enhanced version that incorporates an LLM module to automate fuzzing.
