Color Image Cryptosystem Based on Sine Chaotic Map, 4D Chen Hyperchaotic Map of Fractional-Order and Hybrid DNA Coding
نویسندگان
چکیده
With advancements in computer and communication technologies, the production, utilization applications of digital images is at an unprecedented rate. Recent include military communications, remote sensing, novel engineering designs storage as well medical imaging. In most cases, such convey highly sensitive or confidential information, which creates a strong need for design secure robust color image cryptosystems. literature has shown that fractional-order functions exhibit improved performance over their corresponding integer-order versions. This especially true use processing applications. this research work, we make four-dimensional (4D) hyperchaotic Chen map fractional-order, conjunction with sine chaotic hybrid DNA coding algorithm. A thorough numerical analysis presented, showcasing security efficiency proposed cryptosystem. Performance gauged terms resilience against visual, histogram, statistical, entropy, differential, brute-force attacks. Mean values metrics computed are follows. MSE 9396, PSNR 8.27 dB, information entropy 7.997, adjacent pixel correlation coefficient 0, NPCR 99.62%, UACI 33, MAE 80.57, very large key space 2 744 . The cryptosystem exhibits low computational complexity, it encrypts rate 4.369 Mbps. Furthermore, passes NIST SP 800 suite tests successfully. Comparison those reported state-of-the-art by counterpart algorithms show comparable superior values.
منابع مشابه
Image encryption based on chaotic tent map in time and frequency domains
The present paper is aimed at introducing a new algorithm for image encryption using chaotic tent maps and the desired key image. This algorithm consists of two parts, the first of which works in the frequency domain and the second, in the time domain. In the frequency domain, a desired key image is used, and a random number is generated, using the chaotic tent map, in order to change the phase...
متن کاملA Novel Color Image Cryptosystem Using Chaotic Cat and Chebyshev Map
With the advancement of multimedia and real-time networks, a vast number of digital images are now stored and transmitted over public networks. A lot of researches of chaos-based image encryption technologies have been done. However, the performance of conventional encryption algorithm is not satisfying when used to color image. In this paper, we propose an improved chaos-based color image cryp...
متن کاملA Cryptosystem Using Expansion of Chaotic Map
A chaotic map has sensitivity to a change in initial conditions and parameters, and a long-term forecast becomes impossible by iterations of a chaotic map. These features look similar to the properties of the cryptology. For that reason, it is effective to use chaotic maps for cryptosystems. In this research, we propose a cryptosystem using iterations of a chaotic map. This cryptosystem uses ex...
متن کاملA Color Image Encryption Algorithm Based on a Fractional-Order Hyperchaotic System
In this paper, a new color image encryption algorithm based on a fractional-order hyperchaotic system is proposed. Firstly, four chaotic sequences are generated by a fractional-order hyperchaotic system. The parameters of such a system, together with the initial value, are regarded as the secret keys and the plain image is encrypted by performing the XOR and shuffling operations simultaneously....
متن کامل4D MAP MRI Image Reconstruction
Conventional MRI reconstruction techniques are susceptible to artifacts when imaging moving organs. In this paper, a reconstruction algorithm is developed that accommodates respiratory motion instead of using only navigator-gated data. The maximum a posteriori (MAP) algorithm uses the raw k-space time-stamped data and the 1D diaphragm navigator signal to reconstruct the images and estimate defo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2023
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2023.3282160