A novel image encryption/decryption scheme based on chaotic neural networks

Bigdeli, Nooshin; Farid, Yousef; Afshar, Karim

doi:10.1016/j.engappai.2012.01.007

Cited by 77 publications

(28 citation statements)

References 23 publications

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“…Recently, many encryption schemes based on chaos have been proposed , including schemes for grey-level images [3][4][5][6][7]27] and the schemes for colour images [8][9][10][11][12][13][14]20,26,[34][35][36]. Inevitably, most of them have proven to be insecure because the trajectories in low dimension chaotic systems are periodic for finite precisions in digital computers [15,17,18,21,28,33].…”

Section: Introductionmentioning

confidence: 99%

A Colour Image Encryption Scheme Using Permutation-Substitution Based on Chaos

Wang

Zhang

Bao

2015

Entropy

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An encryption scheme for colour images using a spatiotemporal chaotic system is proposed. Initially, we use the R, G and B components of a colour plain-image to form a matrix. Then the matrix is permutated by using zigzag path scrambling. The resultant matrix is then passed through a substitution process. Finally, the ciphered colour image is obtained from the confused matrix. Theoretical analysis and experimental results indicate that the proposed scheme is both secure and practical, which make it suitable for encrypting colour images of any size.

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Section: Introductionmentioning

confidence: 99%

A Colour Image Encryption Scheme Using Permutation-Substitution Based on Chaos

Wang

Zhang

Bao

2015

Entropy

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“…Up to now, many chaotic cryptosystems have been proposed [9][10][11][12][13][14][15][16]. However, most of them are proved to be insecure.…”

Section: Introductionmentioning

confidence: 99%

A novel image encryption scheme based on 2-D logistic map and DNA sequence operations

2015

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This paper proposes a novel image encryption scheme based on DNA sequence operations and chaotic system. Firstly, two-dimensional logistic chaotic map is employed to modify each pixel of the image, and then, the DNA encoding rules are adopted to encode and generate a DNA matrix. Secondly, pseudo-random sequences generated by twodimensional logistic map are transformed into another DNA matrix. Thirdly, DNA addition, subtraction and complementary rules are used to control the operations between two DNA matrices for obtaining the ciphered results. Finally, the ciphered image is obtained by decoding the DNA matrix formulations into binary formulations. Experimental results and theoretical analysis show that the scheme is extraordinarily high secure to resist various attacks.

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“…Nooshin Bigdeli et al, [7] presented an image encryption algorithm based on chaotic neural network (CNN). The employed CNN is comprised of two 3-neuron layers called chaotic neuron layer (CNL) and permutation neuron layer (PNL).…”

Section: Related Workmentioning

confidence: 99%

Fractional Bio-Image Encryption using Karhunen-Loeve Transform

Sivakumar¹,

Venkatesan²

2013

IJCA

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Bio-images such as fingerprint, face and iris are sensitive and hence small change in such images could affect the result substantially. The processing overhead could be reduced by encrypting a preferred region instead of encrypting the entire image. In this paper a novel fractional bio-image encryption method is presented using Karhunen-Loeve (KL) transform, which is a reversible linear transform. The original image (x) is given as input to cropping function to identify and extract the region to be encrypted. Next, the extracted region, in the form of square, is given as input to the KL transform which in turn produces the cipher image (y) and the inverse transform key (T). The encrypted region is combined with the original image to get the partial cipher image. Since the inverse transform key (T) plays a major role for decryption, it could be given to the receiver by encrypting with symmetric key cryptosystem. On receiving the partial encrypted image (y) the receiver identify and extract the encrypted region and apply the inverse of KL transform using the inverse key (T). The result is merged with the received image to get the original image (x). The histograms of the encrypted portion of the images are nearly uniform and different from the histogram of original images. This method of fractional bioimage cryptosystem will reduce the overhead of encryption and decryption processes.

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A novel image encryption/decryption scheme based on chaotic neural networks

Cited by 77 publications

References 23 publications

A Colour Image Encryption Scheme Using Permutation-Substitution Based on Chaos

A Colour Image Encryption Scheme Using Permutation-Substitution Based on Chaos

A novel image encryption scheme based on 2-D logistic map and DNA sequence operations

Fractional Bio-Image Encryption using Karhunen-Loeve Transform

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