Colour image encryption scheme based on enhanced quadratic chaotic map

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Colour image encryption scheme based on enhanced quadratic chaotic map

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In this study, an enhanced quadratic map (EQM) is proposed and has been applied in a new colour image encryption scheme. The performance evaluations show that the EQM has excellent performances such as better Lyapunov exponent and larger chaotic ranges when compared with the classical quadratic map. The sequences generated from this EQM are successfully used in a new proposed colour image encryption scheme with excellent confusion and diffusion properties. The encryption structure is based on the permutation–diffusion process, and then adopted on the classical permutation, it is characterised by a high speed of diffusion, which enables the encryption of the three components of the plaintext image at the same time, and these encrypted components are simultaneously related to each other. The proposed scheme is tested on the USC-SIPI image dataset and on the real-life image dataset; its effectiveness is also compared with five latterly proposed image encryption schemes. The simulation results indicate that the proposed scheme has the properties of large key space, a weaker correlation between neighbouring pixels, higher sensitivity towards key, greater randomness of pixels and the capacity to withstand statistical analysis, plaintext/chosen-plaintext attacks, and differential attacks, thus that it has higher security and can be appropriate for image encryption.

Inspec keywords: cryptography; chaos; chaotic communication; statistical analysis; image colour analysis; image processing

Other keywords: larger chaotic ranges; encryption structure; plaintext image; image encryption schemes; enhanced quadratic map; encrypted components; excellent confusion; real-life image dataset; colour image encryption scheme; classical quadratic map; enhanced quadratic chaotic map; EQM; diffusion properties; USC-SIPI image dataset

Subjects: Cryptography; Optical, image and video signal processing; Data security; Computer vision and image processing techniques

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