Search in my way: Practical outsourced image retrieval framework supporting unshared key

• Main Authors: WANG, Xiangyu, MA, Jianfeng, LIU, Ximeng, MIAO, Yinbin
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2019
• 主題: Content-based image retrieval; Multi-source data sharing; Privacy-preserving; Unshared key; Computer and Systems Architecture; Digital Communications and Networking
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/4424

The traditional privacy-preserving image retrieval schemes not only bring large computational and communication overhead but also cannot well protect the image and query privacy in multi-user scenarios. To solve the above problems, we first propose a basic privacy-preserving content-based image retrieval (CBIR) framework which significantly reduces storage and communication overhead compared with the previous works. Furthermore, we design a new efficient key conversion protocol to support unshared key multi-owner multi-user image retrieval without losing search precision. Moreover, our framework supports unbounded attributes and can trace malicious users according to leaked secret keys, which significantly improve the usability of multi-source data sharing. Strict security analysis shows that the user privacy and outsourced data security can be guaranteed during the image retrieval process, and the performance analysis using real-world dataset shows that the proposed image retrieval framework is efficient and feasible for practical applications.