Study Reveals Privacy Risks in Multimodal RAG Systems
A new empirical study investigates privacy risks in multimodal Retrieval-Augmented Generation (mRAG) pipelines, focusing on vision-centric tasks like visual question answering. The research demonstrates that standard model prompting can determine whether a specific image is included in the mRAG database and, if present, leak associated metadata such as captions. The findings underscore the need for privacy-preserving mechanisms in mRAG systems. The study's code is publicly available online. The paper is published on arXiv under computer science and cryptography.
Key facts
- Multimodal RAG pipelines for vision tasks pose privacy risks.
- Attack can determine if an image is in the mRAG database.
- Attack can leak metadata like captions.
- Study uses standard model prompting.
- Code is published online.
- Paper is on arXiv.
- Focus is on membership inference and image caption retrieval.
- Highlights need for privacy-preserving mechanisms.
Entities
Institutions
- arXiv