PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 6, 2026PeerJ Computer Science0 citationsOpen Access

A block-wise cyclic shifting-based reversible data hiding scheme (BCS-RDH) for secure medical image transmission

View Full Paper
MMManikandan Vazhora MalayilPRPartha Pratim RoySAShakeel Ahmed

Key Points

  • To enhance the security of medical image transmission through a novel reversible data hiding method.
  • Introducing block-wise cyclic shifting-based reversible data hiding (BCS-RDH)
  • Embedding additional data in encrypted images using partition-based operations
  • Conducting experimental studies on standard images to analyze key parameters.
  • BCS-RDH achieves a concealing rate of (Log 2 S 2 )/ S 2 bits per pixel.
  • It retains the histogram and entropy of encrypted images during data embedding.
  • The method outperforms several existing reversible data hiding approaches.

Abstract

Reversible data hiding (RDH) has received serious attention from researchers in the past few years. The RDH method that can store additional details in encrypted images is a challenging area since the concealing rate is too low for such approaches. This research work introduces a new RDH method called block-wise cyclic shifting-based RDH (BCS-RDH), which can embed additional data in an image through a block-wise right cyclic shifting operation on the partitions of size S × S pixels. The BCS-RDH can embed any integer value in the range 0−( S 2 −1) and it ensures a concealing rate of (Log 2 S 2 )/ S 2 bits per pixel (bpp). The BCS-RDH ensures the retention of the histogram and entropy of the encrypted image since the spatial rearrangement does not alter these two parameters, ensuring that the RDH process does not compromise the security aspects. The image reconstruction and the retrieval of the hidden details are done at the recipient by analyzing all the left-cyclic shifted partitions after attempting the decryption. The experimental study is carried out on standard images, and we rigorously analyzed all the key parameters. The study shows that the BCS-RDH surpasses several existing well-known RDH approaches.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Malayil et al. (2026) studied this question.

synapsesocial.com/papers/69fa8e3804f884e66b5307echttps://doi.org/10.7717/peerj-cs.3709
Ask AI
Helpful
Bookmark
Share
View Full Paper