[2506.10030] Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment

Computer Science > Cryptography and Security arXiv:2506.10030 (cs) [Submitted on 10 Jun 2025 (v1), last revised 28 Feb 2026 (this version, v2)] Title:Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment Authors:Tianyu Chen, Jian Lou, Wenjie Wang View a PDF of the paper titled Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment, by Tianyu Chen and 2 other authors View PDF HTML (experimental) Abstract:As Retrieval-Augmented Generation (RAG) evolves into service-oriented platforms (Rag-as-a-Service) with shared knowledge bases, protecting the copyright of contributed data becomes essential. Existing watermarking methods in RAG focus solely on textual knowledge, leaving image knowledge unprotected. In this work, we propose AQUA, the first watermark framework for image knowledge protection in Multimodal RAG systems. AQUA embeds semantic signals into synthetic images using two complementary methods: acronym-based triggers and spatial relationship cues. These techniques ensure watermark signals survive indirect watermark propagation from image retriever to textual generator, being efficient, effective and imperceptible. Experiments across diverse models and datasets show that AQUA enables robust, stealthy, and reliable copyright tracing, filling a key gap in multimodal RAG protection. Subjects: Cryptography and Security (cs.CR); Artificial Intelligence (cs.AI) Cite as: arXiv:2506.10030 [cs.CR]   (or arXiv:2506.10030v2 [cs.CR]...