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http://dx.doi.org/10.3837/tiis.2020.01.021

UN-Substituted Video Steganography  

Maria, Khulood Abu (Faculty of Science and Information Technology Al-Zaytoonah University of Jordan)
Alia, Mohammad A. (Faculty of Science and Information Technology Al-Zaytoonah University of Jordan)
Alsarayreh, Maher A. (Faculty of Science and Information Technology Al-Zaytoonah University of Jordan)
Maria, Eman Abu (Faculty of Science and Information Technology Al-Zaytoonah University of Jordan)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.14, no.1, 2020 , pp. 382-403 More about this Journal
Abstract
Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.
Keywords
Information Hiding; Stego-Key; Exact Matching Algorithm; and Key-Dependent Data Technique;
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