Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

Abstract

Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

Reversible data hiding for encrypted image based on adaptive prediction error coding

“…As digital images are widely used in our lives, researchers have designed many image-based RDH algorithms. According to the meanings of visual contents of digital images, these RDH algorithms can be divided into two kinds: RDH algorithms for plaintext image [9][10][11] and RDH algorithms for encrypted image [12][13][14][15]. In this work, we study a novel RDH algorithm for encrypted image.…”

Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction

“…The receiver can obtain the original image, secret data or both under specific authority. Generally, there are mainly three RDHEI frameworks, namely reserving room before encryption (RRBE) [19][20][21][22][23][24][25], vacating room after encryption (VRAE) [26][27][28][29][30][31][32] and vacating room by encryption (VRBE) [33][34][35][36][37][38][39][40].…”

“…Due to mean value preservation, data extraction and image recovery can be performed perfectly. Yu et al [24] encrypted the pre-processed image generated by prediction and conducted data hiding with additive homomorphism. Nguyen et al [25] selected smooth pixels according to a given threshold and four neighboring pixels before encryption.…”