Journal of King Saud University: Computer and Information Sciences (Jan 2023)

BPPIR: Blockchain-assisted privacy-preserving similarity image retrieval over multiple clouds

  • Miao Tian,
  • Yushu Zhang,
  • Youwen Zhu,
  • Wei Wang,
  • Qihui Wu,
  • Yong Xiang

Journal volume & issue
Vol. 35, no. 1
pp. 324 – 334

Abstract

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With the progress of the times and the development of electronic products, more and more images are captured and stored on multiple cloud servers, which are more likely to exhibit dishonesty because of interdependence rather than semi-honesty and thus how to achieve search over multiple clouds becomes intractable. Moreover, most of the existing research works on content-based image retrieval so far do not consider dishonest clouds and thereby do not support multi-cloud retrieval. On the one hand, a central search server is generally introduced for the convenience of retrieval in the system with multiple cloud servers. However, the central search server may return false or incomplete search results for possible commercial profit, which reduces the retrieval accuracy. On the other hand, cloud servers may destroy the image integrity by deleting or tampering images to save computing and bandwidth resources, resulting in the loss of important information for the image owner and incorrect decryption of the image for the user. In order to address these two problems, we propose a blockchain-assisted privacy-protected similarity image retrieval in the multiple cloud environment, which can not only ensure the accuracy of the retrieval results, but also can verify the integrity of images. The performance of this scheme is evaluated on a real-world dataset, and the results show the high retrieval precision and efficiency of this scheme.

Keywords