A Self-Adaptive Image Encryption Scheme Based on Chaos and Gravitation Model

Qin, Qiuxia; Liang, Zhongyue; Liu, Shuang; Zhou, Changjun

doi:10.1109/access.2023.3267485

Cited by 3 publications

(1 citation statement)

References 43 publications

(45 reference statements)

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“…In the same year, Erkan et al 20 proposed an encryption scheme on chaotic logarithmic maps and key generation using deep convolution neural networks having four operations (permutation, diffusion, DNA encoding, and bit reversion) used in scrambling. In 2023, Qin et al 21 presented an image encryption model using chaos, and a gravitation model was proposed utilizing a self‐adaptive technique. The model consisted of three phases: double scrambling stage, key generation stage, and doubled diffusion stage.…”

Section: Related Workmentioning

confidence: 99%

Multi‐chaotic maps and blockchain based image encryption

Kumari,

Singh,

Singh

2024

Concurrency and Computation

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SummaryThe vast technological developments make data transmission more frequent over networks. So, the data needs to be secured and for that reason, there is a requirement to develop an effective encryption model. This article proposes a novel image encryption model using multi‐chaotic maps and blockchain (MCBE). Chaotic maps have been used in encryption models as chaotic maps have the properties of randomness, and non‐periodicity that get utilized in improving the efficiency of an encryption model. Logistic and tent maps have been employed as multi‐chaotic maps to make the encryption process effective in this work. A logistic map has a simple structure and is easily implementable but has some drawbacks like small keyspace. Keyspace and randomness are enhanced by using a tent map along with a logistic map. The proposed MCBE methodology applies to grayscale or colored images having different file formats and sizes. Initially, in the confusion phase, the permutation of the original image is performed based on a random permutation that changes the original image pixel's position. The encryption model applies multi‐chaotic maps, row‐wise and column‐wise in the diffusion phase to promote the efficiency of the encryption model. Finally, blockchain has been implemented using the SHA‐256 hash function to obtain the encrypted image that enhances the security by increasing the keyspace, to resist brute force attacks. The evaluation performance of the MCBE has been analyzed against various attacks namely statistical attacks, differential attacks, NIST randomness test, noise, and cropping attacks. The evaluated keyspace is which has high key sensitivity with a correlation of encrypted images close to 0. Maximum achieved entropy value of 7.9998, SSIM value between original and encrypted images nearby 0 confirms the dissimilarity. The Number of Pixels Change Rate (NPCR) value of 99.62%, and the value of Unified Average Changed Intensity (UACI) value of 33.54% are within the specified standard range. The calculated correlation coefficient, NPCR, and UACI values have been compared with the existing algorithms, and the results show that the proposed MCBE methodology has better performance than the other state‐of‐the‐art methods. The experimental results indicate that the chaotic ranges generated by multi‐chaotic maps and the SHA‐256 hash function improve the keyspace and security of the encryption model confirming the efficacy of the proposed model MCBE.

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Section: Related Workmentioning

confidence: 99%

Multi‐chaotic maps and blockchain based image encryption

Kumari,

Singh,

Singh

2024

Concurrency and Computation

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Enhanced Security Measures for Image Privacy: Encryption Perspectives

Balaji,

Rahul

et al. 2024

2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)

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Synchronization of Chaotic Extremum-Coded Random Number Generators and Its Application to Segmented Image Encryption

Araki,

Wu,

Yan

2024

Mathematics

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This paper proposes a highly secure image encryption technique based on chaotic synchronization. Firstly, through the design of a synchronization controller, we ensure that the master–slave chaotic extremum-coded random number generators (ECRNGs) embedded in separated transmitters and receivers are fully synchronized to provide synchronized dynamic random sequences for image encryption applications. Next, combining these synchronized chaotic sequences with the AES encryption algorithm, we propose an image segmentation and multi-encryption method to enhance the security of encrypted images and realize a secure image transmission system. Notably, in the design of the synchronization controller, the transient time before complete synchronization between the master and slave ECRNGs is effectively controlled by specifying the eigenvalues of the matrix in the synchronization error dynamics. Research results in this paper also show that complete synchronization of ECRNGs can be achieved within a single sampling time, which significantly contributes to the time efficiency of the image transmission system. As for the image encryption technique, we propose the method of image segmentation and use the synchronized dynamic random sequences generated by the ECRNGs to produce the keys and initialization vectors (IVs) required for AES-CBC image encryption, greatly enhancing the security of the encrypted images. To highlight the contribution of the proposed segmented image encryption, statistical analyses are conducted on the encrypted images, including histogram analysis (HA), information entropy (IE), correlation coefficient analysis (CCA), number of pixels change rate (NPCR), and unified average changing intensity (UACI), and compared with existing literature. The comparative results fully demonstrate that the proposed encryption method significantly enhances image encryption performance. Finally, under the network transmission control protocol (TCP), the synchronization of ECRNGs, dynamic keys, and IVs is implemented as well as segmented image encryption and transmission, and a highly secure image transmission system is realized to validate the practicality and feasibility of our design.

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A Self-Adaptive Image Encryption Scheme Based on Chaos and Gravitation Model

Cited by 3 publications

References 43 publications

Multi‐chaotic maps and blockchain based image encryption

Multi‐chaotic maps and blockchain based image encryption

Enhanced Security Measures for Image Privacy: Encryption Perspectives

Synchronization of Chaotic Extremum-Coded Random Number Generators and Its Application to Segmented Image Encryption

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