Secure Image-Authentication Schemes With Hidden Double Random-Phase Encoding

Yi, Faliu; Kim, You-Hyun; Moon, Inkyu

doi:10.1109/access.2018.2880730

Cited by 13 publications

(15 citation statements)

References 35 publications

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“…However, due to the characteristics of digital images, such as large data volume and strong correlation between adjacent pixels, traditional ciphers are not suitable for encrypting images [2]. Accordingly, image encryption algorithms based on technologies such as DNA random coding [4], double random phase coding [5,6], Arnold transform [7], and chaotic systems [8][9][10] have been proposed.…”

Section: Introductionmentioning

confidence: 99%

An Image Encryption Scheme Based on Lorenz Hyperchaotic System and RSA Algorithm

Lin

2021

Security and Communication Networks

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This research proposes a new image encryption scheme based on Lorenz hyperchaotic system and Rivest–Shamir–Adleman (RSA) algorithm. Firstly, the initial values of the Lorenz hyperchaotic system are generated by RSA algorithm, and the key stream is produced iteratively. In order to change the position and gray value of the pixel, the image data are hidden by additive mode diffusion. Secondly, the diffusion image matrix is reshaped into a one-dimensional image matrix, which is confused without repetition to hide the image data again. Then, the finite field diffusion algorithm is executed to realize the third hiding of the image information. In order to diffuse the pixel information into the entire cipher image, the additive mode diffusion algorithm needs to be looped twice. Finally, the cipher image can be obtained. The experimental results prove that the image encryption scheme proposed in this research is effective and has strong antiattack and key sensitivity. Moreover, the security of this encryption scheme relies on the RSA algorithm, which has high security.

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Section: Introductionmentioning

confidence: 99%

An Image Encryption Scheme Based on Lorenz Hyperchaotic System and RSA Algorithm

Lin

2021

Security and Communication Networks

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“…DRPE, as a popular optical security approach, has been researched extensively because of the easy configuration and parallel processing properties [26][27][28]. DRPE has also been widely used in image authentication, information hiding, and watermarking [29][30][31][32][33]. Figure 1 presents a graphic diagram of a DRPE method in the Fourier domain.…”

Section: Double Random Phase Encodingmentioning

confidence: 99%

“…The second random phase mask, m2, is positioned in the Fourier domain. For DRPE implemented in other domains, such as the Fresnel, Gyrator, and Fractional Fourier domains, the random phase mask m1 remains in the input image plane, whereas the second random phase mask, m2, is placed at the corresponding domain [30]. The computational implementation of DRPE in the Fourier domain can also be written mathematically as…”

Section: Double Random Phase Encodingmentioning

confidence: 99%

“…The original DRPE technique is achieved in the Fourier domain, whereas several other variations are implemented in different domains, such as the Fresnel domain, fractional Fourier domain, and gyrator transform domain [26][27][28]. The DRPE algorithm has been studied extensively and used widely in image encryption, authentication, and watermarking [29][30][31][32]. A previous study [33] claimed that the DRPE algorithm could be a good encryption algorithm in an IoT system for energy-constrained devices, while a secure key exchange scheme is proposed for image cryptography.…”

Section: Introductionmentioning

confidence: 99%

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Privacy-Preserving Image Classification With Deep Learning and Double Random Phase Encoding

Jeong

Moon

2021

IEEE Access

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With the emergence of cloud computing, large amounts of private data are stored and processed in the cloud. On the other hand, data owners (users) may not want to reveal data information to cloud providers to protect their privacy. Therefore, users may upload encrypted data to the cloud or thirdparty platforms, such as Google Cloud, Amazon Web Service, and Microsoft Azure. Conventionally, data must be decrypted before being analyzed in the cloud, which raises privacy concerns. Moreover, decryption of big data such as images requires enormous computation resources, which is unsuitable for energyconstrained devices, particularly Internet of Things (IoT) devices. Data privacy in most popular applications, such as image query or classification, can be preserved if encrypted images can be directly classified on the cloud or IoT devices without decryption. This paper proposes a high-speed double random phase encoding (DRPE) technique of encrypting images into white-noise images. DRPE-encrypted images are then uploaded and stored in the cloud. Images that are encrypted without being decrypted are classified using deep convolutional neural networks in the cloud. The simulation results indicated the feasibility and good performance of the proposed approach. The proposed privacy-preserving image classification method can be useful in data-sensitive fields, such as medicine and transportation.

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“…In [23][24][25], DRPE was mixed with photon-counting imaging to acquire sparse complex information and secure image authentication based on a statistical nonlinear correlation approach. Since phase information obtained by DRPE and photoncounting imaging is sparse and requires less space to store, it has been favored by other studies [22,[26][27][28][29]. To reduce storage and provide higher security, the schemes [22,26] only reserved partial phase information for the authentication.…”

Section: Introductionmentioning

confidence: 99%

Secure Image Authentication Scheme Using Double Random-Phase Encoding and Compressive Sensing

Ren

Niu

Fan

et al. 2021

Security and Communication Networks

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Double random-phase encoding- (DRPE-) based compressive sensing (CS) systems support image authentication for noisy images. When extending such systems to resource-constrained applications, how to ensure the authentication strength for noisy images becomes challenging. To tackle the issue, an efficient and secure image authentication scheme is presented. The phase information of the plain image is generated using DRPE and quantized into a binary image as the authentication information. Meanwhile, a sparser error matrix generated by the same plain image and vector quantization (VQ) image works as the input of CS. The authentication information and VQ indexes are self-hidden into the quantized measurements to construct the combined image. Then, it is permutated and diffused with the chaotic sequences generated from a modified Henon map. After decryption at the receiver side, the verifier can implement the blind authentication between the noisy decoded image and the reconstructed image. Supported by the detailed numerical simulations and theoretical analyses, the DRPE-CSVQ exhibits more powerful compression and authentication capability than its counterpart.

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Secure Image-Authentication Schemes With Hidden Double Random-Phase Encoding

Cited by 13 publications

References 35 publications

An Image Encryption Scheme Based on Lorenz Hyperchaotic System and RSA Algorithm

An Image Encryption Scheme Based on Lorenz Hyperchaotic System and RSA Algorithm

Privacy-Preserving Image Classification With Deep Learning and Double Random Phase Encoding

Secure Image Authentication Scheme Using Double Random-Phase Encoding and Compressive Sensing

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