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Arabian Journal for Science and Engineering
Erschienen in: Arabian Journal for Science and Engineering 4/2020

04.07.2019 | Research Article - Special Issue - Intelligent Computing and Interdisciplinary Applications

Hiding Shares of Counting-Based Secret Sharing via Arabic Text Steganography for Personal Usage

verfasst von: Adnan Gutub, Khaled Alaseri

Erschienen in: Arabian Journal for Science and Engineering | Ausgabe 4/2020

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Abstract

This paper presented new models to hide sensitive data via Arabic text steganography. The models are structured 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 original secret sharing process are challenging to be memorized unlike normal password assignment that is enjoying the full personal selection. Therefore, our models for hiding 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 redundant 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 Imam Nawawi’s forty hadeeth collected by Islamic Scholar: Yahya ibn Sharaf an-Nawawi as standard text statements (40 Prophet Hadiths) showing interesting results and promising research contributions.
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Metadaten
Titel
Hiding Shares of Counting-Based Secret Sharing via Arabic Text Steganography for Personal Usage
verfasst von
Adnan Gutub
Khaled Alaseri
Publikationsdatum
04.07.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Arabian Journal for Science and Engineering / Ausgabe 4/2020
Print ISSN: 2193-567X
Elektronische ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-019-04010-6

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