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Related Experiment Video

Updated: Nov 27, 2025

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms
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Reversible Data Hiding Algorithm in Fully Homomorphic Encrypted Domain.

Jingxuan Li1, Xingyuan Liang1, Ceyu Dai1

  • 1College of Information Science and Technology, Jinan University, Guangzhou 510632, China.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel reversible data hiding method using DGHV fully homomorphic encryption. The technique allows direct data embedding into encrypted images, preserving original data integrity.

Keywords:
DGHVcloud computinginformation entropypublic key cryptosystemreversible data hiding

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Area of Science:

  • Cryptography
  • Information Security
  • Digital Image Processing

Background:

  • Data hiding in encrypted images is crucial for privacy.
  • Existing methods often require complex preprocessing.
  • Fully homomorphic encryption offers advanced privacy-preserving computation.

Purpose of the Study:

  • To propose a reversible data hiding scheme using DGHV fully homomorphic encryption.
  • To analyze the feasibility of the scheme from an information entropy perspective.
  • To enable direct data embedding into encrypted images without preprocessing.

Main Methods:

  • Exploiting the DGHV fully homomorphic encryption for data embedding.
  • Utilizing pixel differences and histogram shifting in the encrypted domain.
  • Employing modular arithmetic for data extraction and image restoration.

Main Results:

  • Additional data embedded directly into DGHV encrypted images.
  • Successful extraction of data and restoration of original images.
  • Scheme avoids preprocessing and operates effectively in the encrypted domain.

Conclusions:

  • The proposed scheme offers an effective and efficient method for reversible data hiding in encrypted images.
  • It outperforms previous methods by eliminating preprocessing steps.
  • The approach is validated through extensive testing on standard images.