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

AbstractVarious 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.

Download Full-text

Visual IoT Security: Data Hiding in AMBTC Images Using Block-Wise Embedding Strategy

Sensors ◽

10.3390/s19091974 ◽

2019 ◽

Vol 19 (9) ◽

pp. 1974 ◽

Cited By ~ 3

Author(s):

Yu-Hsiu Lin ◽

Chih-Hsien Hsia ◽

Bo-Yan Chen ◽

Yung-Yao Chen

Keyword(s):

Image Compression ◽

Data Hiding ◽

Smart Cities ◽

Vision System ◽

Transmission Efficiency ◽

Human Vision ◽

Security Issue ◽

Secret Data ◽

Iot Security ◽

Compressed Images

This study investigates combining the property of human vision system and a 2-phase data hiding strategy to improve the visual quality of data-embedded compressed images. The visual Internet of Things (IoT) is indispensable in smart cities, where different sources of visual data are collected for more efficient management. With the transmission through the public network, security issue becomes critical. Moreover, for the sake of increasing transmission efficiency, image compression is widely used. In order to respond to both needs, we present a novel data hiding scheme for image compression with Absolute Moment Block Truncation Coding (AMBTC). Embedding secure data in digital images has broad security uses, e.g., image authentication, prevention of forgery attacks, and intellectual property protection. The proposed method embeds data into an AMBTC block by two phases. In the intra-block embedding phase, a hidden function is proposed, where the five AMBTC parameters are extracted and manipulated to embed the secret data. In the inter-block embedding phase, the relevance of high mean and low mean values between adjacent blocks are exploited to embed additional secret data in a reversible way. Between these two embedding phases, a halftoning scheme called direct binary search is integrated to efficiently improve the image quality without changing the fixed parameters. The modulo operator is used for data extraction. The advantages of this study contain two aspects. First, data hiding is an essential area of research for increasing the IoT security. Second, hiding in compressed images instead of original images can improve the network transmission efficiency. The experimental results demonstrate the effectiveness and superiority of the proposed method.

Download Full-text

Two-Layer Reversible Data Hiding for VQ-Compressed Images Based on De-Clustering and Indicator-Free Search-Order Coding

Future Internet ◽

10.3390/fi13080215 ◽

2021 ◽

Vol 13 (8) ◽

pp. 215

Author(s):

Chin-Chen Chang ◽

Jui-Feng Chang ◽

Wei-Jiun Kao ◽

Ji-Hwei Horng

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

State Of The Art ◽

Secret Data ◽

Compressed Images ◽

Hide Information ◽

Search Order ◽

Using Data ◽

Free Search ◽

Index Table

During transmission of digital images, secret messages can be embedded using data hiding techniques. Such techniques can transfer private secrets without drawing the attention of eavesdroppers. To reduce the amount of transmitted data, image compression methods are widely applied. Hiding secret data in compressed images is a hot issue recently. In this paper, we apply the de-clustering concept and the indicator-free search-order coding (IFSOC) technique to hide information into vector quantization (VQ) compressed images. Experimental results show that the proposed two-layer reversible data hiding scheme for IFSOC-encoded VQ index table can hide a large amount of secret data among state-of-the-art methods with a relatively lower bit rate and high security.

Download Full-text

Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy

Mathematical Problems in Engineering ◽

10.1155/2013/476181 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11

Author(s):

Jiann-Der Lee ◽

Yaw-Hwang Chiou ◽

Jing-Ming Guo

Keyword(s):

Vector Quantization ◽

Data Hiding ◽

Reversible Data Hiding ◽

Embedding Capacity ◽

Bit Rate ◽

Secret Data ◽

Compressed Images ◽

Search Order ◽

High Embedding Capacity ◽

Embedding Rate

A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) compressed image and achieve lossless reconstruction of a vector-quantization- (VQ-) compressed image. The rather random distributed histogram of a VQ-compressed image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit rate scenarios are deposited. More specifically, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is superior to those of the former data hiding schemes for VQ-based, VQ/SMVQ-based, and search-order-coding- (SOC-) based compressed images.

Download Full-text

A novel data hiding and reversible scheme using SMN blocks in VQ-compressed images

Opto-Electronics Review ◽

10.2478/s11772-011-0012-8 ◽

2011 ◽

Vol 19 (2) ◽

Author(s):

C. Huang ◽

W. Wang ◽

S. Wang

Keyword(s):

Vector Quantization ◽

Data Hiding ◽

Reversible Data Hiding ◽

Multimedia Security ◽

Experimental Results ◽

Compression Rate ◽

Secret Data ◽

Compressed Images ◽

Reversible Method ◽

The Relationship

AbstractData hiding is a technique for embedding secret data into cover media. It is important to multimedia security and has been widely studied. Reversible data hiding methods are becoming prevalent in the area because they can reconstruct the original cover image while extracting the embedded data. In this paper, we propose a new reversible method for vector quantization (VQ) compressed images. Our method takes advantages of the relationship among the side match neighbouring (SMN) blocks to achieve reversibility. The experimental results show that the proposed method has higher compression rate and larger capacity than other existing reversible methods.

Download Full-text

Asymmetric Data Hiding for Compressed Images with High Payload and Reversibility

Symmetry ◽

10.3390/sym13122355 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2355

Author(s):

Juan Lin ◽

Chin-Chen Chang ◽

Ji-Hwei Horng

Keyword(s):

Information Security ◽

Data Hiding ◽

Research Area ◽

Step Size ◽

Secret Data ◽

Stego Image ◽

Compressed Images ◽

Security Research ◽

Pixel Value

Hiding secret data in digital images is an attractive topic in the information security research area. Because the data-embedded stego image looks exactly the same as a regular image, transmitting secret data with stego images does not draw the attention of eavesdroppers, thus fulfilling the goal of information security. Many reversible data hiding (RDH) methods for absolute moment block truncation coding (AMBTC) compressed images have been proposed. These methods hide secret data in an AMBTC-compressed image to produce a stego image and transmit it to the recipient. Upon receiving the stego image, the recipient can extract the secret data and recover the AMBTC-compressed image. In this paper, we propose an RDH scheme for AMBTC-compressed images with an asymmetric embedding rule. Using the AMBTC-compressed version as the basis, the proposed embedding scheme always modifies a pixel value toward its original value with a step size (bitrate) proportional to the gap width. Therefore, the visual quality of the stego image is better than the referred AMBTC version. Additionally, as a result of the adaptive bitrate strategy, the data embedding capacity of the proposed scheme outperforms that of state-of-the-art methods. The security of the resulting stego images was also tested by RS-steganalysis. Experimental results show that the overall performance of the proposed scheme is satisfactory. We revised it, please confirm.

Download Full-text

A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189877 ◽

2021 ◽

pp. 1-11

Author(s):

Kusan Biswas

Keyword(s):

Data Hiding ◽

High Capacity ◽

Error Correcting Codes ◽

Human Vision ◽

Data Embedding ◽

Compressed Images ◽

Matrix Encoding ◽

Dct Coefficients ◽

Capacity Data ◽

Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

Download Full-text

Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

Entropy ◽

10.3390/e23070917 ◽

2021 ◽

Vol 23 (7) ◽

pp. 917

Author(s):

Limengnan Zhou ◽

Hongyu Han ◽

Hanzhou Wu

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Hot Spot ◽

Data Embedding ◽

Histogram Shifting ◽

Secret Data ◽

Content Selection ◽

Wide Range ◽

Map Generation ◽

Content Adaptive

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

Download Full-text

Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

Applied Sciences ◽

10.3390/app11156741 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6741

Author(s):

Chia-Chen Lin ◽

Thai-Son Nguyen ◽

Chin-Chen Chang ◽

Wen-Chi Chang

Keyword(s):

Data Hiding ◽

Free Space ◽

Reversible Data Hiding ◽

Secret Message ◽

Embedding Capacity ◽

Absolute Moment ◽

Compressed Images ◽

High Embedding Capacity ◽

Significant Attention ◽

Efficiency Rate

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

Download Full-text

Energy challenges in optical access and aggregation networks

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2014.0435 ◽

2016 ◽

Vol 374 (2062) ◽

pp. 20140435 ◽

Cited By ~ 8

Author(s):

Daniel C. Kilper ◽

Houman Rastegarfar

Keyword(s):

Optical Networks ◽

Optical Switching ◽

Energy Use ◽

Future Internet ◽

Critical Issue ◽

Optical Systems ◽

The Internet ◽

Total System ◽

Single Chip ◽

Processor Core

Scalability is a critical issue for access and aggregation networks as they must support the growth in both the size of data capacity demands and the multiplicity of access points. The number of connected devices, the Internet of Things, is growing to the tens of billions. Prevailing communication paradigms are reaching physical limitations that make continued growth problematic. Challenges are emerging in electronic and optical systems and energy increasingly plays a central role. With the spectral efficiency of optical systems approaching the Shannon limit, increasing parallelism is required to support higher capacities. For electronic systems, as the density and speed increases, the total system energy, thermal density and energy per bit are moving into regimes that become impractical to support—for example requiring single-chip processor powers above the 100 W limit common today. We examine communication network scaling and energy use from the Internet core down to the computer processor core and consider implications for optical networks. Optical switching in data centres is identified as a potential model from which scalable access and aggregation networks for the future Internet, with the application of integrated photonic devices and intelligent hybrid networking, will emerge.

Download Full-text

Reversible Data Hiding in Encrypted Images Using Median Edge Detector and Two’s Complement

Symmetry ◽

10.3390/sym13060921 ◽

2021 ◽

Vol 13 (6) ◽

pp. 921

Author(s):

Rui Wang ◽

Guohua Wu ◽

Qiuhua Wang ◽

Lifeng Yuan ◽

Zhen Zhang ◽

...

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Personal Information ◽

Rapid Development ◽

Prediction Method ◽

Prediction Errors ◽

Edge Detector ◽

Secret Data ◽

Encrypted Images ◽

Cloud Servers

With the rapid development of cloud storage, an increasing number of users store their images in the cloud. These images contain many business secrets or personal information, such as engineering design drawings and commercial contracts. Thus, users encrypt images before they are uploaded. However, cloud servers have to hide secret data in encrypted images to enable the retrieval and verification of massive encrypted images. To ensure that both the secret data and the original images can be extracted and recovered losslessly, researchers have proposed a method that is known as reversible data hiding in encrypted images (RDHEI). In this paper, a new RDHEI method using median edge detector (MED) and two’s complement is proposed. The MED prediction method is used to generate the predicted values of the original pixels and calculate the prediction errors. The adaptive-length two’s complement is used to encode the most prediction errors. To reserve room, the two’s complement is labeled in the pixels. To record the unlabeled pixels, a label map is generated and embedded into the image. After the image has been encrypted, it can be embedded with the data. The experimental results indicate that the proposed method can reach an average embedding rate of 2.58 bpp, 3.04 bpp, and 2.94 bpp on the three datasets, i.e., UCID, BOSSbase, BOWS-2, which outperforms the previous work.

Download Full-text