A Comprehensive Analysis Method for Reversible Data Hiding in Stream-Cipher-Encrypted Images

Reversible data hiding in encrypted images (RDHEI), an essential branch of reversible data hiding (RDH), has been in development for more than a decade. For most existing stream-cipher-based RDHEI algorithms, encryption schemes are often not the same; thus, these schemes have different effects on the encrypted images. As a result, it is not reasonable to compare the embedding rates (ERs) of RDHEI algorithms directly as we do for plaintext RDH algorithms. However, to our knowledge, many studies focus on the performance of embedding but neglect the influence of the encryption. To compare the performance of stream-cipher-based RDHEI algorithms more reasonably, this paper proposes a novel comprehensive measure to evaluate state-of-the-art RDHEI algorithms. First, the characteristics of the stream-cipher-based RDHEI algorithms are divided into two categories according to the encryption and embedding processes. Next, we use correlation and redundancy to evaluate the influence of encryption schemes and also use ER, computation complexity, visual quality, and algorithm stability to evaluate the embedding schemes. In the end, in order to combine all six indexes into the final evaluation measure, we standardize each index before applying the radar chart. The experimental results show the evaluation results of the recent RDHEI algorithms via a comprehensive analysis and demonstrate the guiding significance of the proposed method for the current RDHEI algorithm selection.

Automated summary

This paper proposes a novel comprehensive measure to evaluate the performance of stream-cipher-based reversible data hiding algorithms, taking into consideration the influence of encryption schemes. By categorizing the characteristics of encryption and embedding processes, and using correlation, redundancy, embedding rate, computation complexity, visual quality, and algorithm stability as evaluation indexes, this method provides a more reasonable comparison of RDHEI algorithms. The experimental results demonstrate the guiding significance of the proposed method for current RDHEI algorithm selection.