Shuliang Sun, "Chaotic image encryption scheme using two-by-two deoxyribonucleic acid complementary rules," Abstract. An image encryption technique has been proposed using deoxyribonucleic acid (DNA) operations and chaotic map in this scheme. First, initial conditions of row encryption and column encryption are calculated. Then, a two-dimensional sine iterative chaotic map with infinite collapse (ICMIC) modulation map (2D-SIMM) is adopted to produce chaotic sequences. Extended exclusive OR (XOR) is executed to enhance security. A mask matrix is produced by 2D-SIMM. It performs XOR operation with the DNA-encoded matrix. Finally, the revised DNA-encoded matrix is performed two-by-two DNA complementary rules and executed DNA decoding to obtain the cipher image. Experiment results prove that the proposed scheme is secure enough and can resist various attacks. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
The quality of image encryption is commonly measured by the Shannon entropy over the ciphertext image. However, this measurement does not consider to the randomness of local image blocks and is inappropriate for scrambling based image encryption methods. In this paper, a new information entropy-based randomness measurement for image encryption is introduced which, for the first time, answers the question of whether a given ciphertext image is sufficiently random-like. It measures the randomness over the ciphertext in a fairer way by calculating the averaged entropy of a series of small image blocks within the entire test image. In order to fulfill both quantitative and qualitative measurement, the expectation and the variance of this averaged block entropy for a true-random image are strictly derived and corresponding numerical reference tables are also provided. Moreover, a hypothesis test at significance α-level is given to help accept or reject the hypothesis that the test image is ideally encrypted/random-like. Simulation results show that the proposed test is able to give both effectively quantitative and qualitative results for image encryption. The same idea can also be applied to measure other digital data, like audio and video./ Information Sciences 00 (2018) 1-23 2 Since then, research on the sequence cipher published many excellent ciphers, including Blowfish [8] in 1993, Twofish [28] in 1998 and advanced encryption standard (AES) [3] in 1998. Nowadays, these encryption algorithms still prevail and are used by thousands of people, organizations and companies.As the other side of the coin, cryptography analysis developed at the same time as data encryption.Many ciphers are considered to be insecure due to some undesired properties that are weak to some cryptography analysis. For example, DES is believed to be insecure as it is weak to the differential attack and the bruteforce attack [34]. Many of these attacks, such as the frequency attack, ciphertext-only attack and known ciphertext attack are designed directly for weak ciphertext, which is not random-like. Therefore, the ability of generating random-like ciphertext is one of most crucial criteria for a secure cipher.A main focus of testing the randomness of a ciphertext is its distribution. Ideally, this distribution of ciphertext is uniform, because a uniform distribution implies that the each symbol in ciphertext is equally important. As a result, the cipher is invulnerable to statistical attacks. Moreover, both the relationship between ciphertext and plaintext and the relationship between ciphertext and encryption key are very complicated and involved. These two properties, namely confusion and diffusion, were identified by Claude Shannon in his 1949 masterpiece paper [30]. Conventionally, randomness tests are designed for binary sequences, for example the Kolmogorov test [32], poker test [32], gap test [32], autocorrelation test [32], Shannon entropy [29], diffusion randomness test [16], etc. Moreover, the standard randomness tests FIPS 140-1[...
In this paper, we propose a so-called probabilistic non-local means (PNLM) method for image denoising. Our main contributions are: 1) we point out defects of the weight function used in the classic NLM; 2) we successfully derive all theoretical statistics of patch-wise differences for Gaussian noise; and 3) we employ this prior information and formulate the probabilistic weights truly reflecting the similarity between two noisy patches. The probabilistic nature of the new weight function also provides a theoretical basis to choose thresholds rejecting dissimilar patches for fast computations. Our simulation results indicate the PNLM outperforms the classic NLM and many NLM recent variants in terms of peak signal noise ratio (PSNR) and structural similarity (SSIM) index. Encouraging improvements are also found when we replace the NLM weights with the probabilistic weights in tested NLM variants.
In this paper, we introduce a symmetric-key Latin square image cipher (LSIC) for grayscale and color images. Our contributions to the image encryption community include 1) we develop new Latin square image encryption primitives including Latin Square Whitening, Latin Square S-box and Latin Square P-box ; 2) we provide a new way of integrating probabilistic encryption in image encryption by embedding random noise in the least significant image bit-plane; and 3) we construct LSIC with these Latin square image encryption primitives all on one keyed Latin square in a new loom-like substitution-permutation network. Consequently, the proposed LSIC achieve many desired properties of a secure cipher including a large key space, high key sensitivities, uniformly distributed ciphertext, excellent confusion and diffusion properties, semantically secure, and robustness against channel noise. Theoretical analysis show that the LSIC has good resistance to many attack models including brute-force attacks, ciphertext-only attacks, known-plaintext attacks and chosen-plaintext attacks. Experimental analysis under extensive simulation results using the complete USC-SIPI Miscellaneous image dataset demonstrate that LSIC outperforms or reach state of the art suggested by many peer algorithms. All these analysis and results demonstrate that the LSIC is very suitable for digital image encryption. Finally, we open source the LSIC MATLAB code under webpage https://sites.google.com/site/tuftsyuewu/source-code.
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