Muhammad Shafique

The paper introduces HarmChip, a novel benchmark to evaluate LLM vulnerability to domain-specific hardware security threats, revealing that current safety guardrails fail against semantically disguised attacks.

The paper introduces RAVEN, a Retrieval-Augmented Vulnerability Exploration Network, which uses LLM agents and RAG to automatically generate comprehensive, structured vulnerability analysis reports for vulnerable code.

The paper proposes a novel Meta-Quantum Ensemble (MQE) framework, which fuses outputs from Quantum Support Vector Machines (QSVMs) and Quantum Neural Networks (QNNs) using a Random Forest meta-learner, significantly improving the robustness and performance of Intrusion Detection Systems.