A visually secure image encryption scheme based on parallel compressive sensing

Wang, Hui; Xiao, Di; Li, Min; Xiang, Yanqiao; Li, Xinyan

doi:10.1016/j.sigpro.2018.10.001

Cited by 152 publications

(76 citation statements)

References 36 publications

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“…To expand the key space and increase the key security, two chaotic maps are employed in this scheme. In the CS phase of the proposed scheme, the Logistic-Tent map [27] is employed to construct a measurement matrix, which is the combination of Logistic map and Skew Tent map, and has superior performance than them. The dynamic equations are as follows:…”

Section: Chaotic Mapsmentioning

confidence: 99%

“…In recent years, CS [23][24][25] exploits far efficiency than the conventional sampling under the Shannon theorem and achieves compression and lightweight encryption simultaneously. Based on Parallel Compressive Sensing(PCS) [26], cryptographic specialists also focus on other technique to combine encryption and compression [27]. However, none of them can verify the participants' identity authentication and achieve tampering and forgery prevention.…”

Section: Introductionmentioning

confidence: 99%

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A Compressive Sensing Based Image Encryption and Compression Algorithm With Identity Authentication and Blind Signcryption

Xiao

Mou

et al. 2020

IEEE Access

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Recently, a robust and secure image sharing scheme with personal identity information embedded was proposed based on Compressive Sensing, Secret Image Sharing and Diffie-Hellman Agreement. However, there exists a security flaw in this scheme. It cannot resist the man-in-the-middle attack in the authentication stage. Anyone can disguise himself as a legal person and get the information when exchanging the secret keys, which provides the possibility for information leakage, tampering, and other attacks. In this paper, we propose an image encryption and compression algorithm with identity authentication and blind signcryption based on Parallel Compressive Sensing (PCS), Secret Sharing(SS) and Elliptic Curve Cryptography (ECC). Firstly, Logistic-Tent system and PCS are employed to complete compression and lightweight encryption in the compression stage. Secondly, random sequences are generated based on Chebyshev map to construct four encryption matrices to perform the encryption process. Meanwhile, the participants' identity authentication and blind signcryption can be achieved by using ECC. Finally, we prove the efficiency and security of the blind signcryption, which can authenticate the participants' identity before restoring the original image. Experiments and security analysis demonstrate that the proposed scheme not only reduce the storage space and computational complexity effectively, but also has resistance against the man-in-the-middle attack, forgery attack and chosen-text attack.

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Section: Chaotic Mapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Compressive Sensing Based Image Encryption and Compression Algorithm With Identity Authentication and Blind Signcryption

Xiao

Mou

et al. 2020

IEEE Access

Self Cite

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“…has proposed an algorithm for bi-level protected CS to encrypt the signal, in which measurement matrix is obtained by product of key-dependent sensing matrix and key-dependent original basis. In the case of parallel CS, an image encryption algorithm has proposed by Wang et al (2019) in which DWT is applied on the plain image to get the sparse representation of the signal. Scrambling is applied on the sparse signal.…”

Section: Literature Reviewmentioning

confidence: 99%

A systematic survey on Image Encryption using Compressive Sensing

Patel¹,

Vaish²

2020

JSR

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In today's world of developing technology, Multimedia transmission through public network is increasing drastically, so there is a need of fast transmission with data security. Compressive Sensing (CS), is a new approach which can acquire the signal in a compressed form. It dimensionally reduces the signal with the help of measurement matrix. Reduction of dimension is totally dependent on the Sparsity. CS has a feature to reconstruct the signal in lesser than the Nyquist sampling rate if the signal is sparse. In the case of transmission, signal security is also a serious concern. CS has an embedded feature of cryptography. It works as a cryptosystem when measurement matrix is shared as a key between the sender and receiver. CS has a vital scope in medical imaging, video acquisition etc. Many researchers have tried to encrypt the signal with the help of different chaos based measurement matrix. This paper gives a detailed survey and critical analysis on the image encryption techniques using CS which can help the naive researchers to excel the field.

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“…is image encryption method camouflages the existence of the original image, thus reducing the possibility of being attacked to a certain extent. As of now, many meaningful image encryption algorithms have been proposed [20][21][22][23][24][25][26][27][28][29][30][31][32][33]. Inspired by [19], the work of [20] embeds multiple color images into nonessential areas of the carrier image to achieve visually meaningful effects.…”

Section: Introductionmentioning

confidence: 99%

“…e algorithm is quite robust but suffers from poor real-time performance and long encryption and decryption times. Compared to [21], the paper [22] uses parallel compressive sensing and integer discrete wavelet transform (IWT) to realize meaningful image encryption, which makes the algorithm more applicable and less time-consuming. However, it was pointed out in [23] that the construction of measurement matrices increases the computational complexity and storage requirements.…”

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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A visually secure image encryption scheme based on parallel compressive sensing

Cited by 152 publications

References 36 publications

A Compressive Sensing Based Image Encryption and Compression Algorithm With Identity Authentication and Blind Signcryption

A Compressive Sensing Based Image Encryption and Compression Algorithm With Identity Authentication and Blind Signcryption

A systematic survey on Image Encryption using Compressive Sensing

Novel Meaningful Image Encryption Based on Block Compressive Sensing

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