Secure Reversible Data Hiding in Encrypted Images based on Classification Encryption Difference
September 26-28, 2022 | Shanghai, China
Authors: Lingfeng Qu (Southwest Jiaotong University), Hadi Amirpour (Alpen-Adria-Universität Klagenfurt), Mohammad Ghanbari (University of Essex, UK), and Christian Timmerer (Alpen-Adria-Universität Klagenfurt), Hongjie He (Southwest Jiaotong University)
Abstract: This paper introduces an algorithm to improve the security, efficiency, and
embedding capacity of reversible data hiding in encrypted images (RDH-EI). It is based on classification encryption difference and adaptive fixed-length coding. Firstly, the prediction error image is obtained, the difference with a bin value greater than the encryption threshold in the difference histogram is found, and it is further modified to obtain the embedding threshold range. Then, under the condition of ensuring that the difference inside and outside the threshold range is not confused, the difference within the threshold is only scrambled, and the difference outside the threshold is scrambled and mod encrypted. After obtaining the encrypted image, an adaptive difference fixed-length coding method is proposed to encode and compress the differences within the threshold. The secret data is embedded in the multiple most significant bits of the encoded difference. Experimental results show that the embedding capacity of the proposed algorithm is improved compared with the state-of-the-art algorithm.