A Color Image Encryption Technique Based on a Substitution-Permutation Network

Mastan, J. Mohamedmoideen Kader; Sathishkumar, G. A.; Bagan, K. Bhoopathy

doi:10.1007/978-3-642-22726-4_54

Cited by 12 publications

(4 citation statements)

References 9 publications

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“…For plaintext sensitivity or key sensitivity, it is high when changing a small number of bits in plaintext or key results in a large variance in ciphertext. As for ciphertext sensitivity, it is embodied when a natural error or intentional tampering in the ciphertext is remarkable [26].…”

Section: Experiments and Performance Analysismentioning

confidence: 99%

TEDL: A Text Encryption Method Based on Deep Learning

Li¹,

Wang

2020

Preprint

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Recent years have seen an increasing emphasis on information security, and various encryption methods have been proposed. However, for symmetric encryption methods, the well-known encryption techniques still rely on the key space to guarantee security and suffer from frequent key updating. Aiming to solve those problems, this paper proposes a novel text encryption method based on deep learning called TEDL, where the secret key includes hyperparameters in deep learning model and the core step of encryption is transforming input data into weights trained under hyperparameters. Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters. Then, a self-update codebook is constructed on the word vector table with the SHA-256 function and other tricks. When communication starts, encryption and decryption are equivalent to indexing and inverted indexing on the codebook, respectively, thus achieving the transformation between plaintext and ciphertext. Results of experiments and relevant analyses show that TEDL performs well for security, efficiency, generality, and has a lower demand for the frequency of key redistribution. Especially, as a supplement to current encryption methods, the time-consuming process of constructing a codebook increases the difficulty of brute-force attacks while not degrade the communication efficiency.

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Section: Experiments and Performance Analysismentioning

confidence: 99%

TEDL: A Text Encryption Method Based on Deep Learning

Li¹,

Wang

2020

Preprint

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“…Specifically, level j + 1 consists of approximation and the details. The details are distributed in three zones: horizontal, vertical, and diagonal [ 15 ].…”

Section: Design Issuesmentioning

confidence: 99%

Efficiency and Flexibility of Fingerprint Scheme Using Partial Encryption and Discrete Wavelet Transform to Verify User in Cloud Computing

Yassin

2014

International Scholarly Research Notices

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Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user's fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user's fingerprint verification.

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“…Along with the Feistel structure, the substitution-permutation network (SPN) structure attains the properties of confusion and diffusion [ 23 ], which are widely employed in both conventional block ciphers [ 24 , 25 ] and chaotic ones [ 26 , 27 , 28 , 29 ]. Typically, the SPN structure can be realized in chaotic ciphers by means of the combination of permutation and diffusion processes, for example, References [ 30 , 31 ]. The advantage of the SPN structure is that the cryptographic statistics can be increased by means of increasing the number of rounds in each of permutation and diffusion processes and/or in a whole.…”

Section: Introductionmentioning

confidence: 99%

Novel Models of Image Permutation and Diffusion Based on Perturbed Digital Chaos

Hoang

Assad

2020

Entropy

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Most of chaos-based cryptosystems utilize stationary dynamics of chaos for the permutation and diffusion, and many of those are successfully attacked. In this paper, novel models of the image permutation and diffusion are proposed, in which chaotic map is perturbed at bit level on state variables, on control parameters or on both. Amounts of perturbation are initially the coordinate of pixels in the permutation, the value of ciphered word in the diffusion, and then a value extracted from state variables in every iteration. Under the persistent perturbation, dynamics of chaotic map is nonstationary and dependent on the image content. The simulation results and analyses demonstrate the effectiveness of the proposed models by means of the good statistical properties of transformed image obtained after just only a single round.

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A Color Image Encryption Technique Based on a Substitution-Permutation Network

Cited by 12 publications

References 9 publications

TEDL: A Text Encryption Method Based on Deep Learning

TEDL: A Text Encryption Method Based on Deep Learning

Efficiency and Flexibility of Fingerprint Scheme Using Partial Encryption and Discrete Wavelet Transform to Verify User in Cloud Computing

Novel Models of Image Permutation and Diffusion Based on Perturbed Digital Chaos

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