VFIRM: Verifiable Fine-Grained Encrypted Image Retrieval in Multi-owner Multi-user Settings
Open accessAbstract
To ensure the security of images outsourced to the malicious cloud without affecting searchability on such outsourced (typically encrypted) images, one could use privacy-preserving Content-Based Image Retrieval (CBIR) primitive. However, conventional privacy-preserving CBIR schemes based on Searchable Symmetric Encryption (SSE) are not capable of supporting efficient fine-grained access control and result verification simultaneously. Therefore, in this article, we propose aVerifiableFine-grained encryptedImageRetrieval scheme in theMulti-owner multi-user settings (VFIRM). VFIRM first utilizes a novel polynomial-based access strategy to provide efficient fine-grained access control. Then, it employs the dual secure$k$-nearest neighbor technique to distribute distinct keys to different data owners and data users, and finally implements an adapted homomorphic MAC technique to check the correctness of search results. Our formal security analysis shows that VFIRM is non-adaptive semantic secure if the client's search key is generated randomly and keeps in secret. Our empirical experiments using two real-world datasets (i.e., Caltech101 and Corel5k) demonstrate the practicality of VFIRM.
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The chaotic system has characteristics of traversal, non-periodicity, high sensitivity to initial conditions and control parameters, and pseudo-randomness, making it suitable for image encryption.
“The chaotic system has the characteristics of traversal, non-periodicity, high sensitivity to the initial conditions and control parameters as well as pseudo-randomness [12], which is suitable to be used for image encryption.”
From Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology (2025) · cites this paper as [12]
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Xu, J., Zhang, J., & Wang, J. (2025) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer20020076 · Cited by 9 · see citing works
- Authors
- Tong, Q., Miao, Y., Chen, L., Weng, J., Liu, X., Choo, K.-K. R., & Deng, R. H.
- Affiliations
- Xidian University (CN)
- Tsinghua University (CN)
- Jinan University (CN)
- Fuzhou University (CN)
- The University of Texas at San Antonio (US)
- Singapore Management University (SG)
- Venue
- IEEE Transactions on Services Computing
- Published
- 2022-11-01
- Volume
- 15
- Issue
- 6
- Pages
- 3606-3619
- ISSN
- 1939-1374 (ISSN-L)
- 2372-0204
- OpenAlex
- W3168139176
- Cited by
- 58
- References
- 39
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 13 · 2023: 11 · 2022: 7 · 2021: 1
- FWCI
- 2.83
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- IEEE Transactions on Services Computing (publishedVersion)
- Singapore Management University Institutional Knowledge (InK) (Singapore Management University) (submittedVersion, other-oa)
- Funders
- National Natural Science Foundation of China (62072361)
- Fundamental Research Funds for the Central Universities (JB211505)
- Guangxi Key Laboratory of Cryptography and Information Security (GCIS201917)
- Guangxi Key Laboratory of Trusted Software (KX202028)
- CCF-Tencent Open Fund WeBank Special Funding (CCF-Webank RAGR 20200102)
- CCF-NSFOCUS Kunpeng Research Fund (CCF-NSFOCUS 20200004)
- Hong Kong Scholar Program (XJ2019038)
- Henan Key Laboratory of Network Cryptography Technology (LNCT2020-A06)
- Cloud Technology Endowed Professorship
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Keywords
- searchable symmetric encryption, fine-grained access control, result verification, semantic security
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