A Secure and Privacy-Preserving Technique Based on Contrast-Enhancement Reversible Data Hiding and Plaintext Encryption for Medical Images

Yang, Yang; Xiao, Xingxing; Cai, Xue; Zhang, Weiming

doi:10.1109/lsp.2020.2965826

Cited by 40 publications

(19 citation statements)

References 25 publications

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“…Next, we use an example illustrated in Figure 9 to demonstrate the coding and compression process. Let the carrier image, A, with a size of m × n be given by m = 14 and n = 1, the grayscale values of A are represented as (163,162,168,166,164,160,124,126,15,13,8,7,9,5), and set the value of b Ele = 4 and b Num = 4 and generate the fragmentation of High 4 and Low 4 by using formula (1). Firstly, transform all the Low 4 into a one-dimensional binary space, B LowConnect = {0011001010000110 .…”

Section: Compressed Redundancy Space-filling Bitsmentioning

confidence: 99%

“…RDH-EI scheme can ensure that the user can retrieve and recover the encrypted image in the plaintext domain, yet empowering that the cloud service providers can accurately extract information from the encrypted image and process it. Additionally, RDH-EI scheme can be further extended to support several real-world applications, such as managing credit records in financial services, court records in government agencies, image processing in military applications, and commercial image processing software [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Wang

Fun

2021

Computers

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Separable Reversible Data Hiding in Encryption Image (RDH-EI) has become widely used in clinical and military applications, social cloud and security surveillance in recent years, contributing significantly to preserving the privacy of digital images. Aiming to address the shortcomings of recent works that directed to achieve high embedding rate by compensating image quality, security, reversible and separable properties, we propose a two-tuples coding method by considering the intrinsic adjacent pixels characteristics of the carrier image, which have a high redundancy between high-order bits. Subsequently, we construct RDH-EI scheme by using high-order bits compression, low-order bits combination, vacancy filling, data embedding and pixel diffusion. Unlike the conventional RDH-EI practices, which have suffered from the deterioration of the original image while embedding additional data, the content owner in our scheme generates the embeddable space in advance, thus lessening the risk of image destruction on the data hider side. The experimental results indicate the effectiveness of our scheme. A ratio of 28.91% effectively compressed the carrier images, and the embedding rate increased to 1.753 bpp with a higher image quality, measured in the PSNR of 45.76 dB.

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Section: Compressed Redundancy Space-filling Bitsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Wang

Fun

2021

Computers

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“…Recently, there is an increasing trend in employing reversible data hiding (RDH) techniques to embed sensitive information into medical images. RHD schemes have found some applications to the medical images, which are reported by Yang et al [ 4 , 5 ]. This shows that RDH is a promising candidate in securing medical images with the additional ability to embed sensitive information, which is not found in traditional cryptographic algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, [ 4 ] had proposed a scheme to embed information into medical images through RDH and homomorphic encryption. Later on, [ 5 ] improved the scheme by proposing a novel paradigm (encrypt-then-RDH) to enhance the security of RDH over medical images.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Reversible Data Hiding for Securing Medical Images

Horng

Chang

et al. 2021

Journal of Healthcare Engineering

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Medical images carry a lot of important information for making a medical diagnosis. Since the medical images need to be communicated frequently to allow timely and accurate diagnosis, it has become a target for malicious attacks. Hence, medical images are protected through encryption algorithms. Recently, reversible data hiding on the encrypted images (RDHEI) schemes are employed to embed private information into the medical images. This allows effective and secure communication, wherein the privately embedded information (e.g., medical records and personal information) is very useful to the medical diagnosis. However, existing RDHEI schemes still suffer from low embedding capacity, which limits their applicability. Besides, such solution still lacks a good mechanism to ensure its integrity and traceability. To resolve these issues, a novel approach based on image block-wise encryption and histogram shifting is proposed to provide more embedding capacity in the encrypted images. The embedding rate is over 0.8 bpp for typical medical images. On top of that, a blockchain-based system for RDHEI is proposed to resolve the traceability. The private information is stored on the blockchain together with the hash value of the original medical image. This allows traceability of all the medical images communicated over the proposed blockchain network.

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“…Because compulsorily hiding unknown data into a cover image will reduce the image quality, data hiding methods can be further classified into the types of reversible data hiding and irreversible data hiding. Reversible data hiding methods [3][4][5][6][7][8] embed secret data into the image, and original image can be recovered from the marked image (i.e., the dataembedded image) during the decoding process. By contrast, irreversible data hiding methods [9][10][11][12][13][14][15] cannot reverse the marked image back to the cover image once data hiding process is completed.…”

Section: Introductionmentioning

confidence: 99%

Security for eHealth system: data hiding in AMBTC compressed images via gradient-based coding

Chen

Kao

et al. 2021

Complex Intell. Syst.

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Various eHealth applications based on the Internet of Things (IoT) contain a considerable number of medical images and visual electronic health records, which are transmitted through the Internet everyday. Information forensics thus becomes a critical issue. This paper presents a data hiding algorithm for absolute moment block truncation coding (AMBTC) images, wherein secret data, or the authentication code, can be embedded in images to enhance security. Moreover, in view of the importance of transmission efficiency in IoT, image compression is widely used in Internet-based applications. To cope with this challenge, we present a novel compression method named gradient-based (GB) compression, which is compatible with AMBTC compression. Therefore, after applying the block classification scheme, GB compression and data hiding can be performed jointly for blocks with strong gradient effects, and AMBTC compression and data hiding can be performed jointly for the remaining blocks. From the experimental results, we demonstrate that the proposed method outperforms other state-of-the-art methods.

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A Secure and Privacy-Preserving Technique Based on Contrast-Enhancement Reversible Data Hiding and Plaintext Encryption for Medical Images

Cited by 40 publications

References 25 publications

Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Separable Reversible Data Hiding in Encryption Image with Two-Tuples Coding

Blockchain-Based Reversible Data Hiding for Securing Medical Images

Security for eHealth system: data hiding in AMBTC compressed images via gradient-based coding

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