In a (k,n) threshold secret image sharing scheme, a secret image is encrypted into n image-shadows that satisfy the following: (1) any less than k image-shadows get no information on the image and (2) any k or more image-shadows can reconstruct the entire image. Cheating problem is an important issue in traditional secret sharing scheme. However, this issue has not been discussed sufficiently in the field of secret image sharing. In this paper, we consider the scenario of cheating behavior in secret image sharing scheme and construct a (k,n) threshold secret image sharing scheme which is capable of cheating detection. Our proposed scheme is able to detect the cheating behavior from up to k − 1 cheaters, and the size of image-shadow is almost same as the image-shadow in the original secret image sharing scheme.

Data hiding is a useful technology to protect secret data through the Internet. Exploiting modification direction (EMD)-based data hiding uses a group of n cover-pixels to embed secret data. It achieves good image quality and high security level of resisting RS detection. However, the embedding capacity of EMD decreases fast when n increases. In 2013, a Generalized EMD (GEMD) was proposed to improve the embedding capacity of EMD, which is always more than 1 bpp (bits per pixel), and keeps the good stego-image quality. In this paper, we propose an enhanced GEMD by dividing a group of n coverpixels into multiple groups. By this method, the embedding capacity can be further improved from GEMD. Our scheme maintains the good image quality and can resist the RS detection as well.

Traditional ( k , n ) secret image sharing provides all-or-nothing decoding model and ( k , n ) scalable secret image sharing provides progress decoding model during image reconstruction. Both these two decoding models are significance in various applications. However, the security level for real applications would change due to the dynamical environment, only one single decoding model cannot satisfy the changeable security requirement. In this work, we construct scalable secret image sharing schemes that provides both all-or-nothing and progress decoding models to satisfy the dynamical secure requirement. Each participant in our schemes only needs to keep one initial-shadow. During image reconstruction, the dealer selects the decoding model according to current security requirement, if progress model is chosen, initial shadows can achieve image reconstruction in progress model without any modification; else if all-or-nothing model is chosen, the dealer does not need to resent new shadows to participants, the initial-shadows can be updated to satisfy all-or-nothing model efficiently.