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Image encryption using a combination of Grain‐128a algorithm and Zaslavsky chaotic map

Authors: Nawel Balaska; Zahir Ahmida; Aïssa Belmeguenaï; Selma Boumerdassi;

Image encryption using a combination of Grain‐128a algorithm and Zaslavsky chaotic map

Abstract

Encryption is a very important way to secure data in storage and communication, and it is a process of encoding messages or information in such a manner that only authorised persons can access it. Different techniques are used to protect confidential image data against illicit access. In image encryption using chaotic systems, most authors use or design algorithms to generate the initial parameters’ values from the secret key. However, as the key size depends on the number of these parameters, the used algorithms show little sensitivity to small changes in the key. To enhance both security and sensitivity in the choice of the initial parameters, this work combines the use of the Grain‐128a stream cipher algorithm with two‐dimensional Zaslavsky chaotic map. Firstly, the Grain‐128a algorithm is applied to generate the required parameters of Zaslavsky's chaotic map from a fixed length 256‐bit secret key. Secondly, the sequences generated by the chaotic map are used to encrypt the image using a bit confusion and diffusion process. The simulation results on greyscale, colour, binary, indexed, and medical images together with the scores obtained in the evaluation of the algorithm show that the proposed method is very sure and effective in encrypting images of any size and any type.

Country
France
Keywords

[INFO] Computer Science [cs]

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    18
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Top 10%
Top 10%
gold