ELSEIR: A Privacy-Preserving Large-Scale Image Retrieval Framework for Outsourced Data Sharing Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.1145/3652583.3658099
Privacy-preserving content-based image retrieval aims to safeguard the security of outsourced private images while maintaining their searchability. However, existing schemes encounter challenges in striking a balance between security, accuracy, and efficiency, as well as difficulties in scaling to large-scale image retrieval in multi-user settings. In this paper, we propose a novel Efficient Large-Scale Encrypted Image Retrieval (ELSEIR) framework for outsourced data sharing. We first utilize a deep hashing model for image feature extraction. Building upon this, we design an irreversible random hash code generation method that incorporates permutation keys for personalized access and integrates differential privacy to further enhance data security. In our multi-user implementation, we distribute the switch keys to the cloud to standardize each key, enabling the accurate search. In addition, we have theoretically proven that our ELSEIR guarantees both outsourced data security and query user privacy. Extensive experiments on real-world datasets demonstrate that our ELSEIR yields comparable accuracy to the unprotected baseline while outperforming existing methods in terms of both retrieval accuracy and efficiency.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3652583.3658099
- https://dl.acm.org/doi/pdf/10.1145/3652583.3658099
- OA Status
- gold
- Cited By
- 4
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399418876
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399418876Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1145/3652583.3658099Digital Object Identifier
- Title
-
ELSEIR: A Privacy-Preserving Large-Scale Image Retrieval Framework for Outsourced Data SharingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-30Full publication date if available
- Authors
-
Zixin Tang, Haihui Fan, Xiaoyan Gu, Yang Li, Bo Li, Xin WangList of authors in order
- Landing page
-
https://doi.org/10.1145/3652583.3658099Publisher landing page
- PDF URL
-
https://dl.acm.org/doi/pdf/10.1145/3652583.3658099Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://dl.acm.org/doi/pdf/10.1145/3652583.3658099Direct OA link when available
- Concepts
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Computer science, Differential privacy, Hash function, Encryption, Image retrieval, Cloud computing, Information retrieval, Data mining, Key (lock), Image (mathematics), Computer security, Artificial intelligence, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4Per-year citation counts (last 5 years)
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25Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2108598243, https://openalex.org/W1557833142, https://openalex.org/W1873763122, https://openalex.org/W4205228770, https://openalex.org/W2132201434, https://openalex.org/W2902688432, https://openalex.org/W3035965352, https://openalex.org/W1973393984, https://openalex.org/W2951457746, https://openalex.org/W2762479434, https://openalex.org/W3094198982, https://openalex.org/W3022522375, https://openalex.org/W1861492603, https://openalex.org/W1999551046, https://openalex.org/W2135074106, https://openalex.org/W2920782418, https://openalex.org/W1976101156, https://openalex.org/W2041480327, https://openalex.org/W2469486851, https://openalex.org/W2563363534, https://openalex.org/W2582843861, https://openalex.org/W1519321993, https://openalex.org/W2623856551, https://openalex.org/W4210879831, https://openalex.org/W3099878876 |
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