Public Key Image Encryption Based on Compressed Sensing

Xie, Dong

doi:10.1109/access.2019.2940996

Cited by 7 publications

(3 citation statements)

References 37 publications

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“…In [3] authors explained into medical image security focused on image encryption and information hiding has grown. In [4] authors explained a simple but efficient method by using matrix multiplication to change the value of a pixel in an image, which made the algorithm very simple but also made it very difficult for intruders to extract the information in the images. In [5] authors described abut 5-D hyperchaotic map actually the result of combining a logistic map with 3D Lorenz, which exhibited dual operating modes.…”

Section: Related Workmentioning

confidence: 99%

Histogram Based Visible Image Encryption for Real Time Applications

Kiran¹,

S²,

Bharath³

et al. 2022

J. Engg. Res. & Sci.

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Like most patient information, medical imaging data is subject to strict data protection and confidentiality requirements. This raises the issue of sending the data which contains a medical image on an open network as per the above issue, also there might be a leakage of information. Encrypting an Image and hiding the information in it is the Potential way of avoiding this problem. But there might be many problems when we try restoring the original image. As a solution to that, an algorithm dealing with region of intrest (ROI) in medical images based on the pixels of interest and histogram peak technique. Firstly Image histogram peak technique is used for calculating peaks in medical images. Then set the Threshold value to segregate the pixels of interest in the medical images. The threshold value can be calculated by taking an average of all peaks in the histogram. These pixels are encrypted with the help of the Sudoku matrix. The proposed scheme will be evaluated using a various test based on statistics along with those results which will be compared to benchmarks of the existing work. We can see the better performance in terms of security from the proposed technique.

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Section: Related Workmentioning

confidence: 99%

Histogram Based Visible Image Encryption for Real Time Applications

Kiran¹,

S²,

Bharath³

et al. 2022

J. Engg. Res. & Sci.

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show abstract

“…For other schemes in [27] and [28], they can complete compression and encryption, but cannot resist the man-in-the-middle attack. The schemes in [7] and [30] can complete encryption, but cannot satisfy identity authenticity and resist the man-in-the-middle attack. For this proposed scheme, it has superior performance, which not only completes compression, encryption and image sharing, but also has the characters of identity authenticity and against the man-in-the-middle attack.…”

Section: H the Performance And Comparisonmentioning

confidence: 99%

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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“…So far, many research results exist that are based on chaotic image encryption, such as the Hopfield chaotic neural network [ 6 , 7 , 8 ], which is a typical dynamic neural network with rich dynamic properties; however, the self-feedback Hopfield network used to generate chaotic phenomena is complex in its structure, computationally intensive with fixed parameters, DNA encryption [ 9 , 10 , 11 , 12 ], DNA computation with huge parallelism, and has huge storage and ultra-low power consumption. The compressed sensing (CS) [ 13 , 14 , 15 , 16 ] compression feature allows multimedia encryption schemes with a much reduced length of ciphertext, and simple linear measurements make the encryption process very efficient. Therefore, CS-based image encryption schemes have also attracted a lot of attention in recent years.…”

Section: Introductionmentioning

confidence: 99%

Plaintext-Related Dynamic Key Chaotic Image Encryption Algorithm

Ping

Sun

et al. 2021

Entropy

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To address the problems of the high complexity and low security of the existing image encryption algorithms, this paper proposes a dynamic key chaotic image encryption algorithm with low complexity and high security associated with plaintext. Firstly, the RGB components of the color image are read, and the RGB components are normalized to obtain the key that is closely related to the plaintext, and then the Arnold transform is used to stretch and fold the RGB components of the color image to change the position of the pixel points in space, so as to destroy the correlation between the adjacent pixel points of the image. Next, the generated sequences are independently encrypted with the Arnold-transformed RGB matrix. Finally, the three encrypted images are combined to obtain the final encrypted image. Since the key acquisition of this encryption algorithm is related to the plaintext, it is possible to achieve one key per image, so the key acquisition is dynamic. This encryption algorithm introduces chaotic mapping, so that the key space size is 10180. The key acquisition is closely related to the plaintext, which makes the ciphertext more random and resistant to differential attacks, and ensures that the ciphertext is more secure after encryption. The experiments show that the algorithm can encrypt the image effectively and can resist attack on the encrypted image.

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Public Key Image Encryption Based on Compressed Sensing

Cited by 7 publications

References 37 publications

Histogram Based Visible Image Encryption for Real Time Applications

Histogram Based Visible Image Encryption for Real Time Applications

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

Plaintext-Related Dynamic Key Chaotic Image Encryption Algorithm

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