Improving steganography for hiding secret sharing

Abstract

In this study, the researcher will develop new models to hide data via Arabic text steganography to hide shares generated from target key within texts to help in the retrieval process. The models are built to serve personal remembrance of secret shares to be used within counting-based secret sharing technique. This research hides secret shares adopting humanized remembrance tool to serve uncontrolled assigned shares which are generated from the security system via automatically authentic target key generation process. The shares in their secret sharing process is a challenge that cannot be memorized unlike the normal password assignment that depends fully on personal selection. Therefore, our models secret shares are proposed to be hidden inside the personally chosen texts utilizing improved Arabic text steganography. This steganography models study is based on Kashida extension character used redundantly within Arabic writing text. The research tests our two proposed modifications to original Arabic text steganography all serving secret sharing on the same text database. The comparisons examined the different models on the same benchmark of 40 standard text statements (40 Prophet Hadiths) showing interesting results and promising research contributions.