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Book ChapterDOI

A novel image encryption framework based on markov map and singular value decomposition

TL;DR: A novel yet simple encryption technique is proposed based on toral automorphism, Markov map and singular value decomposition (SVD) and a reliable decryption scheme is proposed to construct original image from encrypted image.
Abstract: In this paper, a novel yet simple encryption technique is proposed based on toral automorphism, Markov map and singular value decomposition (SVD). The core idea of the proposed scheme is to scramble the pixel positions by the means of toral automorphism and then encrypting the scrambled image using Markov map and SVD. The combination of Markov map and SVD changed the pixels values significantly in order to confuse the relationship among the pixels. Finally, a reliable decryption scheme is proposed to construct original image from encrypted image. Experimental results demonstrate the efficiency and robustness of the proposed scheme.
Citations
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Journal ArticleDOI
TL;DR: A novel yet simple security framework to ensure the confidentiality of medical data during the communication between IoT hops is proposed and utilizes the concept of encryption to ensureThe security.
Abstract: The Internet of Things (IoT) is integrated with the healthcare system to create an intelligent hospital ecosystem. Protecting the privacy and security of medical data is a central problem in such an ecosystem. This article proposes a novel yet simple security framework to ensure the confidentiality of medical data during the communication between IoT hops. The proposed framework utilizes the concept of encryption to ensure the security. It essentially involves inducing confusion among pixels by employing image pixel scrambling achieved by spiralizing the medical data matrix, followed by a diffusion process using matrix exponentials and pseudorandom number generation by sequential chaotic maps. A reliable decryption scheme is finally designed to obtain the original data from the encrypted data. Experimental results and analyzes demonstrate the efficiency and robustness of the proposed framework and, thus, making it more suitable for the IoT ecosystem.

1 citations

Journal Article
TL;DR: Two matrices images, one is the public, and the second is the secret (original) are introduced, which are needed through egovernment data base and the original image is deduced by mutual method of the three public files.
Abstract: Abstract—Image or document encryption is needed through egovernment data base. Really in this paper we introduce two matrices images, one is the public, and the second is the secret (original). The analyses of each matrix is achieved using the transformation of singular values decomposition. So each matrix is transformed or analyzed to three matrices say row orthogonal basis, column orthogonal basis, and spectral diagonal basis. Product of the two row basis is calculated. Similarly the product of the two column basis is achieved. Finally we transform or save the files of public, row product and column product. In decryption stage, the original image is deduced by mutual method of the three public files.

1 citations

References
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Journal ArticleDOI
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Abstract: We propose a new universal objective image quality index, which is easy to calculate and applicable to various image processing applications. Instead of using traditional error summation methods, the proposed index is designed by modeling any image distortion as a combination of three factors: loss of correlation, luminance distortion, and contrast distortion. Although the new index is mathematically defined and no human visual system model is explicitly employed, our experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error. Demonstrative images and an efficient MATLAB implementation of the algorithm are available online at http://anchovy.ece.utexas.edu//spl sim/zwang/research/quality_index/demo.html.

5,285 citations


"A novel image encryption framework ..." refers methods in this paper

  • ...Peak signal to noise ration (PSNR), spectral distortion (SD), normalized singular value similarity (NSvS) [17] and Universal Image Quality Index (UIQ) [ 18 ] are used as the objective metrics to evaluate proposed technique....

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Journal ArticleDOI
TL;DR: The decomposition of A is called the singular value decomposition (SVD) and the diagonal elements of ∑ are the non-negative square roots of the eigenvalues of A T A; they are called singular values.
Abstract: Let A be a real m×n matrix with m≧n. It is well known (cf. [4]) that $$A = U\sum {V^T}$$ (1) where $${U^T}U = {V^T}V = V{V^T} = {I_n}{\text{ and }}\sum {\text{ = diag(}}{\sigma _{\text{1}}}{\text{,}} \ldots {\text{,}}{\sigma _n}{\text{)}}{\text{.}}$$ The matrix U consists of n orthonormalized eigenvectors associated with the n largest eigenvalues of AA T , and the matrix V consists of the orthonormalized eigenvectors of A T A. The diagonal elements of ∑ are the non-negative square roots of the eigenvalues of A T A; they are called singular values. We shall assume that $${\sigma _1} \geqq {\sigma _2} \geqq \cdots \geqq {\sigma _n} \geqq 0.$$ Thus if rank(A)=r, σ r+1 = σ r+2=⋯=σ n = 0. The decomposition (1) is called the singular value decomposition (SVD).

3,036 citations


"A novel image encryption framework ..." refers background in this paper

  • ...In linear algebra, the singular value decomposition(SVD) [ 14 ] is an important factorization of a rectangular real or complex matrix with many applications in signal/image processing and statistics....

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BookDOI
01 Jan 1989

2,186 citations

Journal ArticleDOI
TL;DR: In this Letter, a new image encryption scheme is presented, in which shuffling the positions and changing the grey values of image pixels are combined to confuse the relationship between the cipher-image and the plain-image.

644 citations

Journal ArticleDOI
TL;DR: The experimental results demonstrate that the suggested encryption algorithm of image has the advantages of large key space and high security, and moreover, the distribution of grey values of the encrypted y image has a random-like behavior.

584 citations