A Novel Image Encryption Scheme Using Pixel Shuffler and A5/1

Jolfaei, Alireza; Mirghadri, Abdolrasoul

doi:10.1109/aici.2010.198

Cited by 16 publications

(8 citation statements)

References 13 publications

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“…However, compared to text, much more processing power and bandwidth for processing is required. In recent years a number of different image encryption schemes have been proposed in order to overcome image encryption problems (Lv, Zhang, & Guo, 2009) (Akhshani et al, 2010) (Jolfaei & Mirghadri, 2010a). Due to desirable properties of non-linear dynamical systems such as pseudo-random behavior, sensitivity to initial conditions and ergodicity, the chaos-based encryption has suggested a new and efficient way to deal with the intractable problem of fast and highly secure image encryption.…”

Section: Introductionmentioning

confidence: 99%

Image Encryption Using Chaos and Block Cipher

Jolfaei¹,

Mirghadri²

2010

CIS

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In this paper, a novel image encryption scheme is proposed based on combination of pixel shuffling and new modified version of simplified AES. Chaotic baker's map is used for shuffling and improving S-AES efficiency through S-box design. Chaos is used to expand diffusion and confusion in the image. Due to sensitivity to initial conditions, chaotic baker's map has a good potential for designing dynamic permutation map and S-box. In order to evaluate performance, the proposed algorithm was measured through a series of tests. These tests included visual test and histogram analysis, randomness test, information entropy, encryption quality, correlation analysis, differential analysis and sensitivity analysis. Experimental results show that the new cipher has satisfactory security and is more efficient than AES which makes it a potential candidate for encryption of multimedia data.

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Section: Introductionmentioning

confidence: 99%

Image Encryption Using Chaos and Block Cipher

Jolfaei¹,

Mirghadri²

2010

CIS

Self Cite

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“…17, the Henon map [36] by using Eq. 18, Baker's map [37] in accordance with Eq. (19), the prime modulus multiplicative linear congruential generator (PMMLCG) [38] by using Eq.…”

Section: A Chaotic Map Keyspace Comparisonmentioning

confidence: 96%

Novel Image Encryption Using a Pseudoset Generated by Chaotic Permutation Multicircular Shrinking With a Gradual Deletion of the Input Set

et al. 2020

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High-level security with a large keyspace and a short processing time is needed in digital image encryption. Generally, an encryption method that produces a large keyspace is characterized by a relatively slow encryption process. In this paper, we propose a new image encryption method that uses two chaotic pseudosets. A gradual deletion of the input set (GDIS) is introduced to enhance the process of chaotic permutation multicircular shrinking (CPMCS), herein referred to as GDIS CPMCS, to diffuse the image pixels and control the shift distance of the row and column rotations of an image. The proposed encryption scheme offers some advantages: it has a larger keyspace than the referenced image encryption schemes and a shorter processing time than CPMCS. The processing time of the proposed image encryption method with the GDIS CPMCS algorithm is 16.7 times faster for a gray image and 43 times faster for a color image than that in our previous work. Based on histogram and entropy analyses, the proposed scheme is also robust to statistical analysis. Moreover, the ciphered image has a very high degree of randomness according to the National Institute of Standards and Technology (NIST) randomness test results. In terms of differential analysis, a one-bit change in the original image leads to a substantial change in the ciphered image, as indicated by the unified average change intensity (UACI) and number of pixel change rate (NPCR) scores of 33.45% and 99.61%, respectively. Furthermore, GDIS CPMCS is robust to salt-andpepper, Poisson, Gaussian, and speckle noise, with peak signal-to-noise ratios (PSNRs) higher than 14. The scheme is also robust to data loss since a reconstructed image with 50% data loss can be recognized, as indicated by a PSNR of 11.4 INDEX TERMS cryptography; fast image encryption; very large keyspace; chaotic permutation; robust to noise; multiple circular shrinking

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“…It is expected that the histogram of the encrypted image is uniformly distributed. In this case, it becomes difficult to divide the content of the original image [30]. This coefficient gives us a quantitative indication of the similarity between the original image and the encrypted one [31].…”

Section: Histogrammentioning

confidence: 99%

Privacy Preserving Face Recognition in Cloud Robotics: A Comparative Study

et al. 2021

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Real-time robotic applications encounter the robot on board resources’ limitations. The speed of robot face recognition can be improved by incorporating cloud technology. However, the transmission of data to the cloud servers exposes the data to security and privacy attacks. Therefore, encryption algorithms need to be set up. This paper aims to study the security and performance of potential encryption algorithms and their impact on the deep-learning-based face recognition task’s accuracy. To this end, experiments are conducted for robot face recognition through various deep learning algorithms after encrypting the images of the ORL database using cryptography and image-processing based algorithms.

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A Novel Image Encryption Scheme Using Pixel Shuffler and A5/1

Cited by 16 publications

References 13 publications

Image Encryption Using Chaos and Block Cipher

Image Encryption Using Chaos and Block Cipher

Novel Image Encryption Using a Pseudoset Generated by Chaotic Permutation Multicircular Shrinking With a Gradual Deletion of the Input Set

Privacy Preserving Face Recognition in Cloud Robotics: A Comparative Study

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