Protecting the Sharing and Distribution of Color Images Hosted in Cloud Storage Services

2021 ◽  
Author(s):  
Manuel Cedillo-Hernandez ◽  
David Mata-Mendoza ◽  
Diana Nuñez-Ramirez ◽  
Elizabeth Campos-Ponce ◽  
Eduardo Fragoso-Navarro ◽  
...  
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Cloud Storage ◽  
Research Area ◽  
Color Images ◽  
Promising Solution ◽  
Study Case ◽  
Active Research ◽  
Hidden Data ◽  
Cloud Storage Services

In recent years, the reversible data hiding techniques also known as lossless or invertible data hiding, has gradually become a very active research area. The reversibility of these schemes makes possible to extract the embedded data without errors, as well as to restore the cover medium to its original state. Furthermore, to guarantee the security and confidentiality of the hidden data and the image, reversible data hiding schemes over encrypted domain are presented as a promising solution to solve several issues of information security. This paper presents a study case of reversible data hiding schemes over encrypted domain oriented to the protection of the sharing and distribution of color images hosted in cloud storage services. The experimental results are presented in terms of imperceptibility, capacity, confidentiality, and visual quality, respectively.

Reversible Audio Data Hiding in Spectral and Time Domains

2013 ◽  
pp. 19-41 ◽  
Author(s):  
Akira Nishimura
Keyword(s):  
Data Hiding ◽  
Time Domain ◽  
Reversible Data Hiding ◽  
Linear Prediction ◽  
Data Consistency ◽  
Time Domains ◽  
Audio Data ◽  
Hidden Data ◽  
The Time Domain ◽  
Location Map

Reversible data hiding is a technique whereby hidden data are embedded in host data in such a way that the host data consistency is perfectly preserved and the host data are restored when extracting the hidden data. This chapter introduces basic algorithms for reversible data hiding, histogram shifting, histogram expansion, and compression. This chapter also proposes and evaluates two reversible data hiding methods, i.e., hiding data in the frequency-domain using integer Discrete Cosine Transform (DCT) and modified DCT and hiding in the time domain using linear prediction and error expansion. As no location map is required to prevent amplitude overflow, the proposed method in the time domain achieves a storage capacity of nearly 1 bit per sample of payload data. The proposed methods are evaluated by the payload amount, objective quality degradation of stego signal, and payload concealment.

scholarly journals Reversible Data Hiding Using Inter-Component Prediction in Multiview Video Plus Depth

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 514 ◽  
Author(s):  
Jin Young Lee ◽  
Cheonshik Kim ◽  
Ching-Nung Yang
Keyword(s):  
Video Compression ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Depth Map ◽  
3D Video ◽  
Internet Technology ◽  
Secret Communication ◽  
Multiview Video ◽  
Prediction Error Expansion ◽  
Hidden Data

With the advent of 3D video compression and Internet technology, 3D videos have been deployed worldwide. Data hiding is a part of watermarking technologies and has many capabilities. In this paper, we use 3D video as a cover medium for secret communication using a reversible data hiding (RDH) technology. RDH is advantageous, because the cover image can be completely recovered after extraction of the hidden data. Recently, Chung et al. introduced RDH for depth map using prediction-error expansion (PEE) and rhombus prediction for marking of 3D videos. The performance of Chung et al.’s method is efficient, but they did not find the way for developing pixel resources to maximize data capacity. In this paper, we will improve the performance of embedding capacity using PEE, inter-component prediction, and allowable pixel ranges. Inter-component prediction utilizes a strong correlation between the texture image and the depth map in MVD. Moreover, our proposed scheme provides an ability to control the quality of depth map by a simple formula. Experimental results demonstrate that the proposed method is more efficient than the existing RDH methods in terms of capacity.

scholarly journals A Joint Encryption and Reversible Data Hiding Scheme Based on Integer-DWT and Arnold Map Permutation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Shun Zhang ◽  
Tiegang Gao ◽  
Guorui Sheng
Keyword(s):  
Frequency Domain ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Original Image ◽  
Histogram Modification ◽  
Encrypted Image ◽  
Hidden Data ◽  
Arnold Map

A joint encryption and reversible data hiding (joint encryption-RDH) scheme is proposed in this paper. The cover image is transformed to the frequency domain with integer discrete wavelet transform (integer DWT) for the encryption and data hiding. Additional data is hidden into the permuted middle (LH, HL) and high (HH) frequency subbands of integer DWT coefficients with a histogram modification based method. A combination of permutations both in the frequency domain and in the spatial domain is imposed for the encryption. In the receiving end, the encrypted image with hidden data can be decrypted to the image with hidden data, which is similar to the original image without hidden data, by only using the encryption key; if someone has both the data hiding key and the encryption key, he can both extract the hidden data and reversibly recover the original image. Experimental results demonstrate that, compared with existing joint encryption-RDH schemes, the proposed scheme has gained larger embedding capacity, and the distribution of the encrypted image with data hidden has a random like behavior. It can also achieve the lossless restoration of the cover image.

Reversible data hiding based on Shamir’s secret sharing for color images over cloud

2018 ◽  
Vol 422 ◽  
pp. 77-97 ◽  
Author(s):  
Priyanka Singh ◽  
Balasubramanian Raman
Keyword(s):  
Data Hiding ◽  
Secret Sharing ◽  
Reversible Data Hiding ◽  
Color Images

scholarly journals Two-Bit Embedding Histogram-Prediction-Error Based Reversible Data Hiding for Medical Images with Smooth Area

Computers ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 152
Author(s):  
Ching-Yu Yang ◽  
Ja-Ling Wu
Keyword(s):  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Medical Images ◽  
High Capacity ◽  
Personal Privacy ◽  
Hiding Capacity ◽  
X Ray ◽  
Magnetic Resonance Imaging Mri ◽  
Hidden Data

During medical treatment, personal privacy is involved and must be protected. Healthcare institutions have to keep medical images or health information secret unless they have permission from the data owner to disclose them. Reversible data hiding (RDH) is a technique that embeds metadata into an image and can be recovered without any distortion after the hidden data have been extracted. This work aims to develop a fully reversible two-bit embedding RDH algorithm with a large hiding capacity for medical images. Medical images can be partitioned into regions of interest (ROI) and regions of noninterest (RONI). ROI is informative with semantic meanings essential for clinical applications and diagnosis and cannot tolerate subtle changes. Therefore, we utilize histogram shifting and prediction error to embed metadata into RONI. In addition, our embedding algorithm minimizes the side effect to ROI as much as possible. To verify the effectiveness of the proposed approach, we benchmarked three types of medical images in DICOM format, namely X-ray photography (X-ray), computer tomography (CT), and magnetic resonance imaging (MRI). Experimental results show that most of the hidden data have been embedded in RONI, and the performance achieves high capacity and leaves less visible distortion to ROIs.

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