A comparative study of cellular automata-based digital image scrambling techniques

Jeelani, Zubair; Qadir, Fasel

doi:10.1007/s12530-020-09326-5

Cited by 7 publications

(2 citation statements)

References 26 publications

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“…The ECA was used to extract properties that could be used in a cryptographic diffusion process, while the Henon chaotic map was used in a keyed transposition cipher to produce a shuffled image, which has been shown to be resistant to statistical attacks. In [14], Jeelani et al used cellular automata to scramble digital images. The performance of the algorithm was evaluated in terms of the gray difference degree of the scrambled images.…”

Section: Introductionmentioning

confidence: 99%

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

et al. 2023

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In this work, a color image encryption and decryption algorithm for digital images is presented. It is based on the modular discrete derivative (MDD), a novel technique to encrypt images and efficiently hide visual information. In addition, Langton’s ant, which is a two-dimensional universal Turing machine with a high key space, is used. Moreover, a deterministic noise technique that adds security to the MDD is utilized. The proposed hybrid scheme exploits the advantages of MDD and Langton’s ant, generating a very secure and reliable encryption algorithm. In this proposal, if the key is known, the original image is recovered without loss. The method has demonstrated high performance through various tests, including statistical analysis (histograms and correlation distributions), entropy, texture analysis, encryption quality, key space assessment, key sensitivity analysis, and robustness to differential attack. The proposed method highlights obtaining chi-square values between 233.951 and 281.687, entropy values between 7.9999225223 and 7.9999355791, PSNR values (in the original and encrypted images) between 8.134 and 9.957, the number of pixel change rate (NPCR) values between 99.60851796% and 99.61054611%, unified average changing intensity (UACI) values between 33.44672377% and 33.47430379%, and a vast range of possible keys >5.8459×1072. On the other hand, an analysis of the sensitivity of the key shows that slight changes to the key do not generate any additional information to decrypt the image. In addition, the proposed method shows a competitive performance against recent works found in the literature.

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Section: Introductionmentioning

confidence: 99%

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

et al. 2023

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“…A closed boundary condition (CBC) or a periodic boundary condition (PBC) can be applied to cells at extremes [40]. In CBC, adjacent cells considered naught are those adjacent to the extreme cells [41].…”

Section: Image Scrambling With Camentioning

confidence: 99%

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

Abusham

Ibrahim

Zia

et al. 2022

Scientific Programming

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Systems using biometric authentication offer greater security than traditional textual and graphical password-based systems for granting access to information systems. Although biometric-based authentication has its benefits, it can be vulnerable to spoofing attacks. Those vulnerabilities are inherent to any biometric-based subsystem, including face recognition systems. The problem of spoofing attacks on face recognition systems is addressed here by integrating a newly developed image encryption model onto the principal component pipeline. A new model of image encryption is based on a cellular automaton and Gray Code. By encrypting the entire ORL faces dataset, the image encryption model is integrated into the face recognition system’s authentication pipeline. In order for the system to grant authenticity, input face images must be encrypted with the correct key before being classified, since the entire feature database is encrypted with the same key. The face recognition model correctly identified test encrypted faces from an encrypted features database with 92.5% accuracy. A sample of randomly chosen samples from the ORL dataset was used to test the encryption performance. Results showed that encryption and the original ORL faces have different histograms and weak correlations. On the tested encrypted ORL face images, NPCR values exceeded 99%, MAE minimum scores were over (>40), and GDD values exceeded (0.92). Key space is determined by u 2 s i z e A 0 where A0 represents the original scrambling lattice size, and u is determined by the variables on the encryption key. In addition, a NPCR test was performed between images encrypted with slightly different keys to test key sensitivity. The values of the NPCR were all above 96% in all cases.

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Cellular automata-based digital image scrambling under JPEG compression attack

2021

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A comparative study of cellular automata-based digital image scrambling techniques

Cited by 7 publications

References 26 publications

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

An Integration of New Digital Image Scrambling Technique on PCA-Based Face Recognition System

Cellular automata-based digital image scrambling under JPEG compression attack

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