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International Journal of Nonlinear Analysis and Applications، جلد ۱۳، شماره ۲، صفحات ۱۵۹۱-۱۶۱۵
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عنوان انگلیسی MLCM: An efficient image encryption technique for IoT application based on multi-layer chaotic maps
چکیده انگلیسی مقاله The importance of image encryption has considerably increased especially after the dramatic evolution of the internet of things (IOT) and due to the simplicity of capturing and transferring digital images. Although there are several encryption approaches, chaos-based image encryption is considered the most appropriate approach for image applications because of its sensitivity to initial conditions and control parameters. This research aims at generating an encrypted image free of statistical information to make cryptanalysis infeasible. Therefore, a new method was introduced in this paper called Multi-layer Chaotic Maps (MLCM) based on confusion and diffusion. Basically, the confusion method uses the Sensitive Logistic Map (SLM), Hénon Map, and the additive white Gaussian noise to generate random numbers to be used in the pixel permutation method. However, the diffusion method uses Extended Bernoulli Map (EBM), Tinkerbell, Burgers, and Ricker maps to generate the random matrix. The correlation between adjacent pixels was minimized to have a very small value $(x 10-3)$. Besides, the keyspace was extended to be very large $left(2^{450}right)$ considering the key sensitivity to hinder brute force attack. Finally, a histogram was idealized to be perfectly equal in all occurrences and the resulted information entropy was equal to the ideal value(8), which means that the resulted encrypted image is free of statistical properties in terms of histogram and information entropy. Based on the findings, the high randomness of the generated random sequences of the proposed confusion and diffusion methods is capable of producing a robust image encryption framework against all types of cryptanalysis attacks.
کلیدواژه‌های انگلیسی مقاله IoT applications, Chaotic Maps, Image encryption, Logistic Map, Bernoulli Map
نویسندگان مقاله Kadhum Al-Majdi |
Ashur University College, Baghdad, Iraq

Ahmed Salman |
Department of Computer Technologies Engineering, AL-Esraa University College, Baghdad, Iraq

Noor Alhuda Abbas |
Department of Computer Technologies Engineering, AL-Esraa University College, Baghdad, Iraq

Mohammed Mahdi Hashim |
Faculty of Engineering, Uruk University, Baghdad, Iraq

Mustafa Taha |
Department of Computer Science, Cihan University-Erbil, Kurdistan Region, Iraq

Abdullah Abdulabbas Nahi |
Department of Computer Science, Cihan University-Erbil, Kurdistan Region, Iraq

Salim Saleh |
Department of Computer Science, Cihan University-Erbil, Kurdistan Region, Iraq

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_6571_42e01274c3dcf1568003f3ccf49d9519.pdf
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