Robust secret image sharing scheme resistance to maliciously tampered shadows by AMBTC and quantization.

For (k, n)-threshold secret image sharing (SIS) scheme, only k or more than k complete parts can recover the secret information, and the correct image cannot be obtained if the count of shadow images is not enough or the shadow images are damaged. The existing schemes are weak in resisting large-area shadow image tampering. In this paper, we propose a robust secret image sharing scheme resisting to maliciously tampered shadow images by Absolute Moment Block Truncation Coding (AMBTC) and quantization (RSIS-AQ). The secret image is successively compressed in two ways: AMBTC and quantization. The sharing shadow images contain the sharing results of both compressed image from different parts, so that even the shadow images are faced with large-scale area of malicious tampering, the secret image can be recovered with acceptable visual quality. Compared with related works, our scheme can resist larger area of tampering and yield better recovered image visual quality. The experimental results prove the effectiveness of our scheme.

High capacity data hiding with absolute moment block truncation coding image based on interpolation.

Data hiding is a way of hiding secret data on cover-media and it is used for a variety of applications. An important of the data hiding is to conceal the data in a secret way without loss of cover-media. Until now, continuous research on absolute moment block truncation coding based data hiding methods have improved a performance on data concealment and image quality. However, the current absolute moment block truncation coding based data hiding technology has a limitation in deriving a method that significantly surpasses existing performance. In this paper, we propose a new method to overcome this problem. To do this, first the original image is transformed to the cover image using absolute moment block truncation coding and is expanded the image using neighbor average interpolation algorithm. The proposed three data hiding methods are based on the generated cover image. The first method is to directly replace the pixel value, which is a component of each block, with the same secret value. The second method is to replace the pixels to match the secret bits only for the extended pixels in each block of the cover image. The third method is to apply Hamming code to each block to minimize the number of replacement pixels for data hiding. Experimental results show that our method is superior in terms of efficiency compared to traditional absolute moment block truncation coding based data hiding methods.

Enhance embedding capacity for switch map based multi-group EMD data hiding.

Exploiting Modification Direction (EMD) based data hiding achieves good stego-image quality and high security level. Recently, a section-wise EMD was proposed to enhance the embedding capacity of EMD. Later, Wang et al. introduced a switch map based multi-group EMD to further improve the embedding capacity. However, by a detail observation on the switch map in Wang et al.'s scheme, we find that more codewords with longer code-length can be put into the switch map. In this paper, we build a new switch map by Huffman code, and construct an enhanced multi-group EMD using Huffman code based switch map. Our scheme has higher embedding capacity than Wang et al.'s scheme and other EMD based data hiding methods.

Reducing file size and time complexity in secret sharing based document protection.

Recently, Tu and Hsu proposed a secret sharing based document protecting scheme. In their scheme, a document is encrypted into n shares using Shamir's (k,n) secret sharing, where the n shares are tied in with a cover document. The document reconstruction can be accomplished by acknowledgement of any k shares and the cover document. In this work, we construct a new document protecting scheme which is extended from Tu-Hsu's work. In Tu-Hsu's approach, each inner code of secret document takes one byte length, and shares are generated from all inner codes with the computation in GF(257), where 257 is a Fermat Prime that satisfies 257 = 223+ 1. However, the share size expands when it equals to 255 or 256. In our scheme, each two inner codes of document is combined into one double-bytes inner code, and shares are generated from these combined inner codes with the computation in GF(65537) instead, where 65537 is also a Fermat Prime that satisfies 65537 = 2 24+ 1. Using this approach, the share size in our scheme can be reduced from Tu-Hsu's scheme. In addition, since the number of combined inner codes is half of the inner codes number in Tu-Hsu's scheme, our scheme is capable of saving almost half running time for share generation and document reconstruction from Tu-Hsu's scheme.