Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
February 14, 2026Journal of Multiscale Modelling

Reversible Data Hiding in Encrypted Images with Secret Sharing Using Improved CNN

View Full Paper
Ask AI
Bookmark
Share

Authors

KRK. Upendra RajuESE. Anant SankarCSCh. Sarada

Discussion

Loading...

Member takes

Overview

Experimental results demonstrate improved security and capacity in encrypted images using secret sharing and CNN, indicating a robust solution for secure storage.

Key Points

  • The aim is to enhance reversible data hiding in encrypted images while ensuring security and data integrity.
  • Integrating secret sharing with reversible data hiding in encrypted images
  • Encrypting images before data embedding
  • Utilizing convolutional neural networks for improved embedding capacity
  • Ensuring recovery of original images despite missing or corrupted shares
  • Proposed method outperforms existing reversible data hiding techniques
  • Improved data capacity while maintaining low distortion
  • Enhanced data security and integrity even with missing shares
  • Effective in applications like medical imaging and secure cloud storage

Cite This Study

Raju et al. (2026) studied this question.

synapsesocial.com/papers/6990113f2ccff479cfe57bd1https://doi.org/10.1142/s1756973726400275
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Reversible Data Hiding Algorithm in Encrypted Images Based on Adaptive Median Edge Detection and Matrix-Based Secret Sharing2024
  2. 2Secret Sharing Based Reversible Data Hiding in Encrypted Image with Multiple Data Hiders2024
  3. 3Highly Secure and Adaptive Multisecret Sharing for Reversible Data Hiding in Encrypted Images2025
  4. 4Encrypted image processing using compression and reversible data hiding2024
  5. 5A New Reversible Data Hiding Method Using a Proportional Relation between Peak Signal-to-Noise Ratio and Embedding Capacity on Convolutional Neural Network2024 · 3 citations