Please use this identifier to cite or link to this item:
http://repository.aaup.edu/jspui/handle/123456789/1839
Title: | RGB IMAGE ENCRYPTION ALGORITHM USING 6D HYPERCHAOTIC SYSTEM AND FIBONACCI Q-MATRIX |
Authors: | Younis, Hussein$AAUP$Palestinian Eleyat, Mujahed$AAUP$Palestinian |
Keywords: | Parallelism Multiprocessing RGB Image Encryption 6D Hyperchaotic Chen System Fibonacci Q-Matrix |
Issue Date: | 31-May-2024 |
Publisher: | Journal of Theoretical and Applied Information Technology |
Citation: | Hussein Younis and Mujahed Eleyat, “RGB Image Encryption Algorithm Using 6D Hyperchaotic System And Fibonacci Q-Matrix” Journal of Theoretical and Applied Information Technologyv, 102(10), 2024 |
Abstract: | The advancement of ICT and the widespread use of the Internet enables users to store many types of data via the Internet, and thus these data may be vulnerable to hacking or illegal access. As a result, certain mechanisms must be designed to guarantee that these data are secured. Encryption is one of the most significant methods of image protection as it's based on generating a different image in terms of content from the original image, making it difficult to identify or retrieve the original image only through a key. In this work, an RGB Image Encryption Algorithm Using a 6D Hyperchaotic System and Fibonacci Q-matrix is presented. Confusion and diffusion are used to generate the encrypted image to achieve a high-security level. The proposed encryption algorithm was tested against different types of noise and attacks. Moreover, we combined the proposed algorithm against other algorithms in terms of entropy. The result shows that the proposed algorithm outperformed the existing algorithms. Also, the result shows that the speed up in the execution time of the proposed algorithm can be enhanced up to 2.23x faster by employing parallel programming. |
URI: | http://repository.aaup.edu/jspui/handle/123456789/1839 |
ISSN: | 1992-8645 |
Appears in Collections: | Faculty & Staff Scientific Research publications |
Files in This Item:
File | Description | Size | Format | |
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2Vol102No10.pdf | 1.5 MB | Adobe PDF | ![]() View/Open |
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