No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
arXiv preprint arXiv:2502.00306 , year=
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DP-SynRAG generates reusable differentially private synthetic RAG databases via LLM private prediction to prevent privacy loss accumulation from repeated noise.
ALDEN boosts private data extraction rates from RAG systems by combining active learning for query diversification with dynamic estimation of the underlying knowledge-base topic distribution.
citing papers explorer
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Security Considerations for Multi-agent Systems
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
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Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG)
DP-SynRAG generates reusable differentially private synthetic RAG databases via LLM private prediction to prevent privacy loss accumulation from repeated noise.
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ALDEN: Boosting Private Data Extraction from Retrieval-Augmented Generation Systems via Active Learning and Distribution Estimation
ALDEN boosts private data extraction rates from RAG systems by combining active learning for query diversification with dynamic estimation of the underlying knowledge-base topic distribution.