A Novel Image Encryption Scheme Based on Nonuniform Sampling in Block Compressive Sensing

Zhu, Liya; Song, Huansheng; Zhang, Xi; Yan, Maode; Liang, Zhonghua; Yan, Tao

doi:10.1109/access.2019.2897721

Cited by 40 publications

(21 citation statements)

References 36 publications

(53 reference statements)

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“…To obtain better security performance, sparse representation and traditional approaches were combined. Visually meaningful encryption schemes 22 , 27 , 28 , chaotic map 29 – 36 , cellular automata 37 , 38 , and discrete fractional random transform 39 are some examples.…”

Section: Introductionmentioning

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: Introductionmentioning

confidence: 99%

“…In sparse recovery, the transform which is used to obtain sparse representation has a critical role. Many different transforms, such as wavelet 34 , 40 , DCT 38 , and learned dictionary 35 , were used in different approaches. The transforms also can be categorized into block-based transform 35 and global-based transform 21 , 34 .…”

Section: Introductionmentioning

confidence: 99%

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

Ghaffari

2021

Sci Rep

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“…e process of reconstructing the signal is an optimization problem, and the original signal is reconstructed with high probability from little observations by solving this optimization problem. Following this principle, many image encryption algorithms were developed based on compressive sensing [8][9][10][11][12][13][14][15][16][17][18]. Zhou et al [8] proposed combining high-dimensional chaotic systems to compress and encrypt the image with 2D compressed sensing and then to reencrypt the image by the cyclic shift operation.…”

Section: Introductionmentioning

confidence: 99%

“…In [17], block compression sampling is applied to resource-constrained wireless visual sensor networks (WVSNs), which makes the image more robust when transmitted over unreliable channels. In [18], after the plain image is divided into blocks, the discrete cosine transform is applied to it, and the obtained low frequency, high frequency, and intermediate frequency are observed by different measurement matrices. Following that, forward diffusion, disturbance, and backward diffusion operations are applied to it to generate the final encrypted image.…”

Section: Introductionmentioning

confidence: 99%

Novel Meaningful Image Encryption Based on Block Compressive Sensing

Pan

Huang

et al. 2019

Security and Communication Networks

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is paper proposes a new image compression-encryption algorithm based on a meaningful image encryption framework. In block compressed sensing, the plain image is divided into blocks, and subsequently, each block is rendered sparse. e zigzag scrambling method is used to scramble pixel positions in all the blocks, and subsequently, dimension reduction is undertaken via compressive sensing. To ensure the robustness and security of our algorithm and the convenience of subsequent embedding operations, each block is merged, quantized, and disturbed again to obtain the secret image. In particular, landscape paintings have a characteristic hazy beauty, and secret images can be camou aged in them to some extent. For this reason, in this paper, a landscape painting is selected as the carrier image. After a 2-level discrete wavelet transform (DWT) of the carrier image, the lowfrequency and high-frequency coe cients obtained are further subjected to a discrete cosine transform (DCT). e DCT is simultaneously applied to the secret image as well to split it. Next, it is embedded into the DCT coe cients of the low-frequency and high-frequency components, respectively. Finally, the encrypted image is obtained. e experimental results show that, under the same compression ratio, the proposed image compression-encryption algorithm has better reconstruction e ect, stronger security and imperceptibility, lower computational complexity, shorter time consumption, and lesser storage space requirements than the existing ones.

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“…Image encryption is an important method in information security, and many schemes have been proposed. These algorithms are based on DNA coding [13]- [15], compressive sensing [16]- [19], QR codes [20]- [22], chaotic systems [23]- [32] and others [33]- [38]. Image encryption schemes based on chaotic system are currently very popular.…”

Section: Introductionmentioning

confidence: 99%

A Novel Plaintext-Related Image Encryption Algorithm Based on Stochastic Signal Insertion and Block Swapping

Sun

Guo

2019

IEEE Access

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Image encryption is an important method for protecting private data during communication. This paper proposes a novel hyperchaotic image encryption algorithm based on stochastic signal insertion and block permutation. First, the 5D hyperchaotic system is applied to generate pseudorandom number sequences. The SHA-256 hash function and secret keys are used to produce the initial values of the cryptosystem. The hash values can effectively enhance the sensitivity to plain image. To enlarge the key space and change orbit of cryptosystem, some stochastic signals are inserted during iteration. The plain image is equally divided into two parts. An X-coordinate, a Y-coordinate and a control table are established with produced pseudonumber sequences. The pixel is swapped with another pixel in the current block or another block depending on the control table. Cyclic shift is performed during the diffusion process. Performance and security analyses are executed to verify the effect of the proposed scheme. It is clear that the proposed scheme has a large key space and is highly sensitive to plain image and secret keys. Moreover, the cryptosystem has low computation complexity and can resist correlation analysis, entropy analysis, statistical attack, differential attack, noise and data loss attacks.

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A Novel Image Encryption Scheme Based on Nonuniform Sampling in Block Compressive Sensing

Cited by 40 publications

References 36 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

Novel Meaningful Image Encryption Based on Block Compressive Sensing

A Novel Plaintext-Related Image Encryption Algorithm Based on Stochastic Signal Insertion and Block Swapping

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