Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2022
Abstract
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 a Verifiable Fine-grained encrypted Image Retrieval scheme in the Multi-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 kk-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.
Keywords
Image Retrieval, Encryption, Access Control, Security, Indexes, Feature Extraction, Transform Coding, Privacy Preserving, Content Based Image Retrieval, Fine Grained Access Control, Result Verification
Discipline
Graphics and Human Computer Interfaces | Information Security
Research Areas
Cybersecurity
Areas of Excellence
Digital transformation
Publication
IEEE Transactions on Services Computing
Volume
15
Issue
6
First Page
3606
Last Page
3619
ISSN
1939-1374
Identifier
10.1109/TSC.2021.3083512
Publisher
Institute of Electrical and Electronics Engineers
Citation
TONG, Qiuyun; MIAO, Yinbin; CHEN, Lei; WENG, Jian; CHOO, Kim-Kwang Raymond; LIU, Ximeng; and DENG, Robert H..
VFIRM: Verifiable fine-grained encrypted image retrieval in multi-owner multi-user settings. (2022). IEEE Transactions on Services Computing. 15, (6), 3606-3619.
Available at: https://ink.library.smu.edu.sg/sis_research/10118
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TSC.2021.3083512
