An optimized secret sharing scheme using Hungarian algorithm
Junlan Bai, Ching‐Chun Chang · 2015
The rapid development of network and devices motivates researchers to consider ways of delivering important data securely. In recent decades, secret sharing has attracted more attention, because it encodes the secret data into n shares which will be distributed to n participants, and only qualified participants are available to reconstruct the secret data. In 2012, Kim et al. proposed a novel (2, 2) secret sharing scheme for absolute moment block truncation coding (AMBTC) compressed images. The shadows of their scheme are meaningful images instead of noise-like images. However, the visual quality of the shadows is a little low. In this study, we employ the Hungarian method which is a combinatorial optimization algorithm to permute the secret data for the sake of providing better visual quality of the shadow images. By this way, it can reduce the possibility of suspicion and make the shadow friendlier. Experimental results demonstrated that our scheme offers higher visual quality of the shadows than that of Kim et al.'s.