Image encryption and hiding algorithm based on compressive sensing and random numbers insertion

Ye, Guodong; Pan, Ci; Dong, Youxia; Shi, Yang; Huang, Xiaoling

doi:10.1016/j.sigpro.2020.107563

Cited by 164 publications

(104 citation statements)

References 28 publications

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“…Here, we compare the proposed measurement matrix with the partial Hadamard matrix and the Gaussian random matrix. Partial Hadamard matrix, a famous measurement matrix, has been used in encryption schemes 22,35,38,39,45 . Table 4 shows the effectiveness of these measurement matrices in the proposed encryption process for the different CRs.…”

Section: Resultsmentioning

confidence: 99%

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Image compression-encryption method based on two-dimensional sparse recovery and chaotic system

Ghaffari

2021

Sci Rep

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In this paper, we propose an image compression-encryption method based on two-dimensional (2D) sparse representation and chaotic system. In the first step of this method, the input image is extended in a transform domain to obtain a sparse representation. To achieve better performance of image compression by 2D sparse recovery, the sparse representation is scrambled via a chaotic confusion. This step helps the satisfaction of the uniqueness conditions for sparse recovery, and the security level of encryption is increased. Then, two orthogonal measurement matrices are generated using the chaotic time series. The singular value decomposition is used to compress the sparse scrambled representation in two dimensions. Finally, to reduce the correlation between adjacent pixels in the compressed matrix, and obtain a uniform distribution in the encrypted image, a compressed scrambling matrix based on chaotic confusion is used. Then, XOR operation is applied for final encryption. In the decryption process, to improve the compression efficiency, the total variation constraint is added to the 2D sparse recovery problem based on the smoothed norm. The simulation results demonstrate the satisfying performance of the proposed method for different compression ratios. Security analysis describes the effectiveness of the proposed encryption approach.

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Section: Resultsmentioning

confidence: 99%

“…Usually, CS-based encryption approaches use chaotic systems to generate this matrix. Some approaches construct the measurement matrix based on the combination of the Hadamard transform and chaotic map 22,38,39,45 .…”

mentioning

confidence: 99%

Image compression-encryption method based on two-dimensional sparse recovery and chaotic system

Ghaffari

2021

Sci Rep

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“…The plain image with resolution of × is pre-encrypted and embedded into a host image with resolution of 2 × 2 to obtain a meaningful cipher image, thus increasing the cost of storage and transmission, such as Ref. [29,33].…”

Section: No Other Algorithms Ourmentioning

confidence: 99%

“…In the absence of compression stage, the resolution of the meaningful cipher image is four times that of the plain image, which increases the unnecessary cost of storage and transmission. Later, many improved visually meaningful image encryption algorithms [30][31][32][33][34] have been proposed one after another. Such as Ref.…”

Section: Introductionmentioning

confidence: 99%

Double-Image Visually Meaningful Encryption Algorithm Based on Compressed Sensing and Frft Embedding

Jiang

Liu

Zhu

et al. 2021

Preprint

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The transmission of images via the Internet has grown exponentially in the past few decades. However, the Internet considered as an insecure method of information transmission may cause serious privacy issues. In order to overcome such potential security issues, a novel double-image visually meaningful encryption (DIVME) algorithm conjugating quantum cellular neural network (QCNN), compressed sensing (CS) and fractional Fourier transform (FRFT) is proposed in this paper. First, the wavelet coefficients of the two plain images are scrambled by the Fisher-Yates confusion algorithm, and then compressed by the key-controlled partial Hadamard matrix. The final meaningful cipher image is generated by embedding the encrypted images into a host image with the same resolution of the plain image via the FRFT-based embedding method. Besides, the eigenvalues of the plain images are utilized to generate the key stream to improve the ability of proposed DIVME algorithm to withstand the plaintext attacks. Afterwards, the plaintext eigenvalues are embedded into the alpha channel of the meaningful cipher image under control of the keys to reduce unnecessary storage space and transmission costs. Ultimately, the simulation results and security analyses indicate that the proposed DIVME algorithm is effective and can withstand multiple attacks.

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“…In [36], a compressed sensing strategy based on a semitensor product was proposed and a visual security image encryption scheme was designed. In [37], an image encryption scheme was proposed by using compressive sensing and random number insertion. Zhang et al [38] proposed a plaintext-related image encryption scheme by using perceptron-like network.…”

Section: Introductionmentioning

confidence: 99%

An Effective Chaos‐Based Image Encryption Scheme Using Imitating Jigsaw Method

Peng

Tan

et al. 2021

Complexity

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In this paper, an efficient chaos-based image encryption scheme is proposed, which uses the imitating jigsaw method containing revolving and shifting operations. In this scheme, there are three processes in encryption: preprocessing, encryption process, and postprocessing. In the preprocessing, the original image is partitioned into 64 × 64 pixel image blocks and then randomly revolved and shifted under control sequences which are generated by the hyperchaotic Lorenz system whose initial conditions are calculated by original image and keys. Therefore, the preprocessing is sensitive to plain image against differential attacks. In the encryption process, the after-preprocessing image is partitioned into 32 × 32 pixel image blocks; next they are randomly revolved and encrypted by control sequence and key blocks which are generated by the skew tent map. In postprocessing, the after-encryption image is partitioned into 16 × 16 pixels’ image blocks, and they are randomly revolved and shifted again under control sequences which are related with encrypted image and keys. The postprocessing further increases the diffusion characteristics. Moreover, the test experiment and security analyses are given; the results show that our proposed cryptosystem has both security and speed performance.

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Image encryption and hiding algorithm based on compressive sensing and random numbers insertion

Cited by 164 publications

References 28 publications

Image compression-encryption method based on two-dimensional sparse recovery and chaotic system

Image compression-encryption method based on two-dimensional sparse recovery and chaotic system

Double-Image Visually Meaningful Encryption Algorithm Based on Compressed Sensing and Frft Embedding

An Effective Chaos‐Based Image Encryption Scheme Using Imitating Jigsaw Method

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