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Visual document retrieval indices vulnerable to reconstruction attacks

By PulseAugur Editorial · [3 sources] ·

Researchers have discovered a significant vulnerability in multi-vector visual document retrieval systems, where stored indices can be used to reconstruct original documents. The study, published on arXiv, demonstrates that by inferring necessary components like the encoder and vector order, an attacker can generate document images from their indices. This inversion attack successfully recovers a substantial percentage of words and sensitive tokens, and accurately re-identifies the source page with high probability. While simple protections like token pooling and shuffling offer some mitigation, they are not entirely effective, suggesting that these indices require robust security measures akin to the original documents. AI

IMPACT Highlights potential security risks in AI-powered document retrieval systems, necessitating stronger data protection measures.

RANK_REASON The cluster contains a research paper detailing a novel vulnerability in a specific type of AI system.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

Visual document retrieval indices vulnerable to reconstruction attacks

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COVERAGE [3]

  1. arXiv cs.CL TIER_1 English(EN) · Zhuchenyang Liu, Yao Zhang, Yu Xiao ·

    Inverting Multi-Vector Visual Document Indices

    arXiv:2610.09920v1 Announce Type: cross Abstract: Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party. Since no one can read a page from its vectors, this index is easily treated as l…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Yu Xiao ·

    Inverting Multi-Vector Visual Document Indices

    Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party. Since no one can read a page from its vectors, this index is easily treated as less sensitive than the page. However, because the …

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Inverting Multi-Vector Visual Document Indices

    Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party. Since no one can read a page from its vectors, this index is easily treated as less sensitive than the page. However, because the …

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