MAGMA combines RAG with a stochastic consistency ensemble over dual code embeddings to derive Function Evidence Strength and Evidence Conflict Score metrics, enabling reject-option decisions and achieving 98.4% malware detection.
In: 28th USENIX Security Symposium (USENIX Security 19), pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Quantifiable Uncertainty: A Stochastic Consensus Multi-Agent RAG Framework for Robust Malware Detection
MAGMA combines RAG with a stochastic consistency ensemble over dual code embeddings to derive Function Evidence Strength and Evidence Conflict Score metrics, enabling reject-option decisions and achieving 98.4% malware detection.