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With the rise of cloud computing, large-scale image data from personal, medical, and enterprise archives are often outsourced to cloud servers for efficient storage and computation. To ensure privacy, sensitive images must be encrypted before uploading. Cloud service providers (CSP) offer Database as a Service (DBaaS), including secure image retrieval, for managing encrypted data. Many existing schemes aim to enable privacy-preserving image retrieval but face challenges such as low retrieval efficiency, high computational costs, and limited access control. This paper presents an Efficient and Controllable Privacy-Preserving Image Retrieval (ECPIR) scheme for scenarios using cloud-based database services. We design a hierarchical graph index to organize image vectors in multi-level formats, improving retrieval efficiency. Additionally, we propose a lightweight polynomial-based access control strategy, FastPolyAccess, which uses Fast Fourier Transform (FFT) to enhance computational efficiency and manage access for large-scale user bases. Experimental results show that ECPIR offers superior retrieval performance and robust access control while ensuring privacy.

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ECPIR: Efficient and Controllable Privacy-Preserving Image Retrieval in Cloud-Assisted System

  • 会议论文

  • 发表日期：

    2026年

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  • Mingyue Li,
  • Yuntao Li,
  • Ruizhong Du,
  • Chunfu Jia,
  • Wei Shao

摘要

With the rise of cloud computing, large-scale image data from personal, medical, and enterprise archives are often outsourced to cloud servers for efficient storage and computation. To ensure privacy, sensitive images must be encrypted before uploading. Cloud service providers (CSP) offer Database as a Service (DBaaS), including secure image retrieval, for managing encrypted data. Many existing schemes aim to enable privacy-preserving image retrieval but face challenges such as low retrieval efficiency, high computational costs, and limited access control. This paper presents an Efficient and Controllable Privacy-Preserving Image Retrieval (ECPIR) scheme for scenarios using cloud-based database services. We design a hierarchical graph index to organize image vectors in multi-level formats, improving retrieval efficiency. Additionally, we propose a lightweight polynomial-based access control strategy, FastPolyAccess, which uses Fast Fourier Transform (FFT) to enhance computational efficiency and manage access for large-scale user bases. Experimental results show that ECPIR offers superior retrieval performance and robust access control while ensuring privacy.