ElMouatez Billah Karbab
2 indexed papers
Recent (6 mo)
2With code
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226
Top categories
Crypto×2
Research Timeline
2026
AsmRAG: LLM-Driven Malware Detection by Retrieving Functionally Similar Assembly Code
AsmRAG is a novel framework that improves malware detection by treating it as an evidence-based retrieval task using a code-specialized LLM, achieving high accuracy while providing transparent forensic context.
Quantifiable Uncertainty: A Stochastic Consensus Multi-Agent RAG Framework for Robust Malware Detection
The paper introduces MAGMA, a novel stochastic RAG framework that enhances malware detection by quantifying epistemic uncertainty, achieving a high detection rate of 98.4% against evasion attacks.
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Papers
cs.CRRecentMay 8, 2026
Quantifiable Uncertainty: A Stochastic Consensus Multi-Agent RAG Framework for Robust Malware Detection
The paper introduces MAGMA, a novel stochastic RAG framework that enhances malware detection by quantifying epistemic uncertainty, achieving a high detection rate of 98.4% against evasion attacks.
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cs.CRRecentApr 25, 2026