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Gerald Ketu Ndawula

2 accepted papers

2025

Can LLMs Obfuscate Code? A Systematic Analysis of Large Language Models into Assembly Code Obfuscation

AAAI 2025technical

Malware authors often employ code obfuscations to make their malware harder to detect. Existing tools for generating obfuscated code often require access to the original source code (e.g., C++ or Java), and adding new obfuscations is a non-trivial, labor-intensive process. In this study, we ask the…

2025

Knowledge-Infused Learning for Developing a Mental Health Diagnostic Copilot in Healthcare Systems

AAAI 2025technical

Healthcare diagnostics, especially in underserved communities, faces critical gaps in accessibility and accuracy. African Americans experience significant disparities in mental health care, often receiving delayed or inadequate treatment. This research proposes a diagnostic copilot, an AI-powered as…

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