4.6 Article

Reversible data hiding in encrypted images based on multi-level encryption and block histogram modification

期刊

MULTIMEDIA TOOLS AND APPLICATIONS
卷 76, 期 3, 页码 3899-3920

出版社

SPRINGER
DOI: 10.1007/s11042-016-4049-z

关键词

Signal processing in encrypted domain (SPED); Reversible data hiding in encrypted images (RDH EI); Privacy protection

资金

  1. National Science Foundation of China [61502009, 61525203, 61472235]
  2. China Postdoctoral Science Foundation [2016 M591650]
  3. Shu Guang project - Shanghai Municipal Education Commission
  4. Shanghai Education Development Foundation
  5. Natural Science Foundation of Anhui Province (CN) [1508085SQF216]
  6. Key Program for Excellent Young Talents in Colleges and Universities of Anhui Province [gxyqZD2016011]
  7. Sino-UK Higher Education Research Partnership for PhD studies joint-project - British Council China and the China Scholarship Council (CSC)

向作者/读者索取更多资源

In recent years there has been significant interest in reversible data hiding, and also in particular, reversible data hiding in encrypted images (RDH-EI). This means that additional data can be embedded into a previously encrypted image with no knowledge of the original image content. According to the held keys, legal receivers can get the embedded data or an image very similar to the original one, or, both the embedded data and an image exactly as the original one. In this paper, we propose and evaluate a RDH-EI framework. Firstly, we propose a multi-level encryption (MLE) scheme using both Josephus traversal based multi-granular encryption and a stream cipher. To reduce the quantity of side information required to embed into images together with additional data, we also present a block histogram modification (BHM) approach with self-hidden peak pixels to perform reversible data embedding and a location map marking scheme to perform histogram contraction and recovery. The experimental results demonstrate that, in comparison with other similar methods, the proposed framework achieves improvements in terms of the embedding payload, the decrypted image quality and the accuracy of image restoration.

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