General Meaningful Shadow Construction in Secret Image Sharing

Abstract

Secret image sharing (SIS) is an important technique for image protection. Several shadows are produced in SIS through scrambling pixel values and their correlations of a secret image. We can own sufficient shadows to retrieve the secret image. Meaningful shadow will increase management efficiency as well as decrease encryption suspiciousness. More importantly, it may be applied to encrypted domain searching, which is useful in distributed storage and cloud computing. Hence, the meaningful shadow will save labor and reduce energy consumption. In this paper, based on analyses of the image, SIS, and meaningful shadow, we design a general SIS construction method with meaningful shadow and no pixel expansion, by which and some classic SIS techniques with meaningless (noise-like) shadow some SIS algorithms with meaningful shadow are derived. We take some experiments to demonstrate the effectiveness of our method.