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Fuzzing with Hopper++: Applying LLM to Program Generation and Software Security
This research focuses on leveraging the power of Generative AI and applying Large Language Models to fuzz testing. Based on the previous interpretative fuzzing tool Hopper, this work introduces Hopper++, an enhanced version that incorporates an LLM module to automate fuzzing.
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Wang Hanyu
(She/Her)
student, The University of Hong Kong
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