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The plain image is divided into four subimages which are used for the first diffusion stage. During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. (Brothers Vibe Vibed Piano Dub)[New Boyz Ft Tyga- Active Kingz- NEW 2011!.mp3Ben J (New Boyz) Ft. Tyga & Legacy (New Boyz) Active Kingz (Www.TatekietoRD.CoM).mp3Gustavo Lins - O Grande Amor da Minha Vida(Voz e Piano).mp3Rudy Atwood ao Piano com Quarteto de Cordas Oh amor Infinito.
Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks.
To face these challenges, a wide variety of cryptographic protocols have been proposed in the literature. Consequently, traditional encryptions methods like IDEA, AES, DES, and RSA have limitation in encrypting image such as low efficiency, bulky data, and high correlation among pixels. The digital images have certain characteristics such as redundancy of data, strong correlation among adjacent pixels, robustness against perturbations (i.e., a tiny change in the attribute of any pixel of the image does not drastically degrade the quality of the image), and bulk capacity of data. Cryptography is the science of protecting the privacy of information during communication, under hostile conditions. To secure transmitted information, cryptography techniques are needed.
The advantages of ANN are the ability to generalize results obtained from known situations to unforeseen situations, the fast response time in operational phase, the high degree of structural parallelism, reliability, and efficiency. The development of artificial neural network (ANN) approach is widely used by soft computing techniques that have the capability to capture and model complex input/output relationships of any system. But most of them have been cryptanalysed successfully due to finite computing precision used to represent the floating point output of chaotic system as it introduces cycles in the behavior of chaotic systems and hence becomes vulnerable to attacks. Therefore, chaotic dynamics are expected to provide a fast and easy way for building superior performance cryptosystems. These properties meet some requirements such as a sensitivity to keys, diffusion, and mixing in the sense of cryptography. Moreover, chaos-based and other dynamical systems based algorithms have many important properties such as the sensitive dependence on initial conditions and system parameters, pseudorandom properties, ergodicity, and nonperiodicity.
Mazloom and Eftekhari-Moghadam in have proposed a novel chaos-based cryptosystem for color image encryption operating as a symmetric stream-cipher where the objective is to design a new chaotic algorithm which has the properties of nonlinearity and coupled structure. In , a chaos-based image encryption algorithm with variable control parameters is introduced to improve the deficiency usually obtained by using fixed parameters in the permutation stage which is vulnerable to attacks. In have proposed a new image encryption scheme based on two chaotic logistic maps and external secret key of 80 bits to encrypt the colour image.
But only pixel location is changed to shuffle the whole image which is not sufficient to make the proposed algorithm robust against attacks. They used Hénon map and Lorentz map for pixel shuffling and measured correlation coefficient and key sensitivity for finding the best suited map for this algorithm. In , a new algorithm which utilizes the single logistic map against the four maps used by Nien et al. In order to make it more robust against attacks. In , a modified substitution-diffusion image cipher using chaotic standard and logistic maps is proposed to improve some of the weakness obtained by Patidar et al.
In introduced a new image encryption algorithm based on chaos theory. Wang and He in have developed cryptanalysis on a novel image encryption method based on total shuffling scheme to enhance the security of the scheme based on a novel image encryption method proposed by Zhang and Liu. To improve the diffusion effect, a two-way diffusion process is presented, where one generalized Arnold map and one generalized Bernoulli shift map are utilized to generate two pseudorandom gray value sequences. In the permutation process, he used one generalized Arnold map to generate a chaotic orbit. Ye in has presented a novel chaos-based image encryption scheme with an efficient permutation-diffusion mechanism. In that work, the scheme introduced a significant diffusion effect in permutation procedure through a two-stage bit-level shuffling algorithm by chaotic sequence sorting algorithm and Arnold cat map.
In that algorithm, sixteen rounds are used in the encryption scheme. In have proposed an efficient encryption algorithm for gray image using a secret key of 128 bits without using chaos. Then the diffusion selective encryption process is done on the significant pixels using a secret image key obtained from nonlinear chaotic map space filling curve and singular value decomposition. The core idea of that proposed scheme is to scramble the pixel positions by the means of Saw-Tooth space filling curve followed by the selection of significant pixels using pixels of interest method. Bhatnagar and Wu in have presented an efficient yet simple selective encryption technique based on Saw-Tooth space filling curve, pixels of interest, nonlinear chaotic map, and singular value decomposition.
In , an improved method for fast encryption of images using chaos method is introduced. However, it is performed on higher half pixel bits several times in diffusion stage to substitute pixels. The reversible cellular automata have many advantages such as large evolution rule spaces. In the confusion stage, they shuffle image on unit-level which is a smaller level than pixels by using chaotic maps. Wang and Luan in have combined cellular automata (CA) with chaos to propose a new image encryption. Bahrami and Naderi in have proposed a simple and lightweight stream encryption algorithm for image encryption.
In have presented a novel image encryption/decryption algorithm based on chaotic neural network (CNN). In , a novel image authentication scheme based on hyperchaotic cell neural network (HCCNN) is proposed. Chen and Cai in proposed a neural network-based authentication scheme, which can provide a dynamic and secure remote user authentication over a completely in-secure communication channel. In that work, a large permutation has been generated by combining several small permutations in order to improve the work of Yoon and Kim.
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