An image compression and encryption algorithm based on chaotic system and compressive sensing

Gong, Li-Hua; Qiu, Kaide; Deng, Chengzhi; Zhou, Nanrun

doi:10.1016/j.optlastec.2019.01.039

Cited by 219 publications

(103 citation statements)

References 33 publications

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“…The experimental results indicate that sparse coding method shows better results. Arnold transforms in [6] are used for encrypting the original image and compressive sensing to compress and re-encrypt the resultant encrypted image and with the use of chaotic system measurement matrix is also created. For enhanced security in the proposed algorithm the use of bitwise XOR and pixel scrambling method are considered in order to diffuse and confuse the measurements.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance analysis of compression algorithms for information security: A Review

Sharma

Batra

2018

ICST Transactions on Scalable Information Systems

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Data compression is a vital part of information security, since compressed data is much more secure and convenient to handle. Effective data compression technique creates an effective, secure, easy communicable & redundant data. There are two types of compression algorithmic techniques:-lossy and lossless. These techniques can be applied to any data format like text, audio, video or image file. The primary objective of this study was to analyse data compression techniques used for information security techniques like steganography, cryptography etc. Four each, lossy and lossless techniques are implemented and evaluated on parameters like-file size, saving percentage, time, compression ratio and speed. Detailed analysis shows that the lossy techniques performs better quantitatively whereas lossless is better qualitatively. However, lossless techniques are more effective as there is no data loss during the process. Among all, Huffman encoding outperforms other algorithms.

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Section: Literature Reviewmentioning

confidence: 99%

Performance analysis of compression algorithms for information security: A Review

Sharma

Batra

2018

ICST Transactions on Scalable Information Systems

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“…The chaotic system had a pivotal role in constructing the measurement matrix because their chaotic sequences are random and deterministic signal. Subsequently, Gong et al [2] put forward an image compression and encryption algorithm based on chaotic system, which had a good ability on resistance the known plaintext attacks. However, the measurement matrix was generated from low-dimensional chaotic systems with the simple structures, which greatly reduce the security and the sensitive of the algorithms.…”

Section: Introductionmentioning

confidence: 99%

Color image encryption via compressive sensing and chaotic systems

Zhu

Cheng

2020

MATEC Web Conf.

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In this paper, we design a color image encryption algorithm based on chaotic system and block compressive sensing. Firstly, the sparse representation of the plain-image is obtained by an adaptive learning dictionary. Secondly, the key streams are produced from two excellent lowdimensional chaotic maps, where updating the initial values and parameters rely on the SHA-384 and the input image. Thirdly, three measurement matrices of R, G, B components are constructed from the chaotic sequences, respectively. Finally, a random rows and columns diffusion method is performed on the encrypted image. Experimental results and safety analysis prove that the proposed scheme has excellent performance.

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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%

“…Reference [11] applies compressive sensing to medical images, achieving compression and confidentiality for them. Gong et al [12] used compressive sensing to compress and encrypt images using bitwise XOR operations and pixel scrambling. Compressive sensing greatly improves the efficiency of image compression and encryption, but when large-scale images are observed and reconstructed, the storage space required is large, the computational complexity of the algorithm is high, and the reconstruction time is long.…”

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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An image compression and encryption algorithm based on chaotic system and compressive sensing

Cited by 219 publications

References 33 publications

Performance analysis of compression algorithms for information security: A Review

Performance analysis of compression algorithms for information security: A Review

Color image encryption via compressive sensing and chaotic systems

Novel Meaningful Image Encryption Based on Block Compressive Sensing

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