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Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II)

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 20620

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Prof. Dr. David Megías

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Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Parc Mediterrani de la Tecnologia (edifici B3), 08860 Castelldefels, Spain
Interests: information security and privacy; copyright protection; multimedia content (digital image, audio and video); watermarking; fingerprinting; steganography; signal processing
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Prof. Dr. Wojciech Mazurczyk

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Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland
Interests: information hiding; steganography; network security; traffic measurements; bio-inspired cybersecurity
Special Issues, Collections and Topics in MDPI journals

Dr. Minoru Kuribayashi

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Guest Editor

Center for Data-Driven Science and Artificial Intelligence, Tohoku University, Sendai 980-8577, Japan
Interests: multimedia security; fingerprinting; traitor tracing; signal processing; cryptographic protocol; coding theory; statistical analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content (text, audio, video, etc.) over the Internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. Due to the complementary nature of the general requirements of these methods, i.e., imperceptibility, robustness, security, and capacity, many data hiding schemes aim to elucidate the configuration for optimal performance.

There are many potential applications of data hiding techniques. Copyright protection (via content proof of ownership, owner identification or transaction tracking (fingerprinting), broadcast monitoring, and content authentication, including tampering detection) and localization (copy control, device control, and legacy enhancement) stand out among the applications of digital watermarking. On the other hand, secret communications are the focus of steganography, either for military reasons or for dissidents and criminal organizations. The military and criminal applications of steganography have led to increased interest of the academic community in steganalysis, i.e., the techniques used to detect steganographic communications.

The goal of this Special Issue is to focus on the improvement of data hiding algorithms and their different applications. It will bring together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others, to contribute with original research outcomes that address issues in data hiding algorithms.

Prof. Dr. David Megías
Prof. Dr. Wojciech Mazurczyk
Prof. Dr. Minoru Kuribayashi
Guest Editors

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Keywords

Specific Keywords

Steganography

Steganalysis

Digital watermarking

Zero watermarking

Digital fingerprinting

Coverless data hiding

Reversible data hiding and applications

Forensic aspects of data hiding

Embedding capacity/payload

Emerging applications of data hiding in IoT and Big Data

Applications of data hiding

Generic Keywords

Ownership proof/copyright protection

Covert channels

Traitor-tracing

Embedding capacity

Extraction/detection

Data integrity

Distortion measurement

Transform coding

Information theory

Information entropy

Signal processing

Data segmentation

Published Papers (12 papers)

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Research

41 pages, 7473 KiB

Open AccessArticle

A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT

by Sandra L. Gomez-Coronel, Ernesto Moya-Albor, Jorge Brieva and Andrés Romero-Arellano

Appl. Sci. 2023, 13(14), 8430; https://doi.org/10.3390/app13148430 - 21 Jul 2023

Cited by 3 | Viewed by 1314

Abstract

Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image’s quality is of utmost importance, for example in medical images, where improper embedding of the watermark could change the patient’s diagnosis. On the other hand, in digital images distributed over the Internet, the owner of the images must also be protected. In this work, an imperceptible, robust, secure, and hybrid watermarking algorithm is presented for copyright protection. It is based on the Hermite Transform (HT) and the Discrete Cosine Transform (DCT) as a spatial–frequency representation of a grayscale image. Besides, it uses a block-based strategy and a perfectibility analysis of the best embedding regions inspired by the Human Vision System (HVS), giving the imperceptibility of the watermark, and a Singular-Value Decomposition (SVD) approach improved robustness against attacks. In addition, the proposed method can embed two watermarks, a digital binary image (LOGO) and information about the owner and the technical data of the original image in text format (MetaData). To secure both watermarks, the proposed method uses the Jigsaw Transform (JST) and the Elementary Cellular Automaton (ECA) to encrypt the image LOGO and a random sequence generator and the XOR operation to encrypt the image MetaData. On the other hand, the proposed method was tested using a public dataset of 49 grayscale images to assess the effectiveness of the watermark embedding and extraction procedures. Furthermore, the proposed watermarking algorithm was evaluated under several processing and geometric algorithms to demonstrate its robustness to the majority, intentional or unintentional, attacks, and a comparison was made with several state-of-the-art techniques. The proposed method obtained average values of PSNR = 40.2051 dB, NCC = 0.9987, SSIM = 0.9999, and MSSIM = 0.9994 for the watermarked image. In the case of the extraction of the LOGO, the proposal gave MSE = 0, PSNR ≫ 60 dB, NCC = 1, SSIM = 1, and MSSIM = 1, whereas, for the image MetaData extracted, it gave BER = 0% and

B_{e r r o r} = 0

. Finally, the proposed encryption method presented a large key space (

K = 1.2689 \times 10^{89}

) for the LOGO image. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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19 pages, 5789 KiB

Open AccessArticle

Adversarial Attack for Deep Steganography Based on Surrogate Training and Knowledge Diffusion

by Fangjian Tao, Chunjie Cao, Hong Li, Binghui Zou, Longjuan Wang and Jingzhang Sun

Appl. Sci. 2023, 13(11), 6588; https://doi.org/10.3390/app13116588 - 29 May 2023

Cited by 1 | Viewed by 1547

Abstract

Deep steganography (DS), using neural networks to hide one image in another, has performed well in terms of invisibility, embedding capacity, etc. Current steganalysis methods for DS can only detect or remove secret images hidden in natural images and cannot analyze or modify secret content. Our technique is the first approach to not only effectively prevent covert communications using DS, but also analyze and modify the content of covert communications. We proposed a novel adversarial attack method for DS considering both white-box and black-box scenarios. For the white-box attack, several novel loss functions were applied to construct a gradient- and optimizer-based adversarial attack that could delete and modify secret images. As a more realistic case, a black-box method was proposed based on surrogate training and a knowledge distillation technique. All methods were tested on the Tiny ImageNet and MS COCO datasets. The experimental results showed that the proposed attack method could completely remove or even modify the secret image in the container image while maintaining the latter’s high quality. More importantly, the proposed adversarial attack method can also be regarded as a new DS approach. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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26 pages, 8599 KiB

Open AccessArticle

A Novel Adaptive Image Data Hiding and Encryption Scheme Using Constructive Image Abstraction

by Chi-Feng Lan, Chung-Ming Wang and Woei Lin

Appl. Sci. 2023, 13(10), 6208; https://doi.org/10.3390/app13106208 - 18 May 2023

Viewed by 887

Abstract

Image abstraction simplifies complex images, highlights specific features, and preserves different levels of structures to achieve a desired style. This paper presents a constructive and adjustable data hiding algorithm to convey various secret messages and resist modern steganalytic attacks. Our scheme produces an abstracted stego image, while synthesizing an original image during the image abstraction process. Our algorithm is flexible, applicable to two types of images: high-dynamic-range images and ordinary color images, aka low-dynamic-range images. Additionally, we introduce a novel image encryption scheme suitable for the above two types of images, which incorporates a two-dimensional logistic tent modular map and a bit-level random permutation technique, thereby further protecting the content of the stego image and the carried secret messages. Compared with the current state-of-the-art methods, our algorithm provides a 14% to 33% larger embedding rate, while lowering the distortion of the abstracted stego image. A comprehensive security analysis confirmed that our algorithm provides high security to resist statistical, differential, brute force, chosen-plaintext, and chosen key attacks. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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20 pages, 41605 KiB

Open AccessArticle

A Hybrid Watermarking Approach for DICOM Images Security

by Mayssa Tayachi, Laurent Nana, Anca Christine Pascu and Faouzi Benzarti

Appl. Sci. 2023, 13(10), 6132; https://doi.org/10.3390/app13106132 - 17 May 2023

Cited by 1 | Viewed by 1002

Abstract

A hybrid watermarking approach for DICOM medical image protection is proposed in this paper. The medical image is first separated into two parts: the region used for the diagnosis, called Region Of Interest (ROI), and the remaining, called Region Of Non-Interest (RONI). The patient’s name is then extracted from the header of the DICOM image and pertinent features from the ROI. These data are therefore used to construct a watermark based on a Jacobian model. On the one hand, this watermark is used for the zero watermarking of the ROI. On the other hand, it is divided into blocks that are embedded in the RONI using a linear interpolation technique. Experiment results show a good performance of the proposed approach. The average values of SSIM, PSNR, NC, and BER are respectively 0.98, 71 dB, 0.98, and 0.0054, and the watermark embedding and extraction times do not exceed 12 s. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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24 pages, 4779 KiB

Open AccessArticle

Multi-Hider Reversible Data Hiding Using a Weighted Color Transfer and Modulus Operation

by Ku-Sung Hsieh and Chung-Ming Wang

Appl. Sci. 2023, 13(2), 1013; https://doi.org/10.3390/app13021013 - 11 Jan 2023

Cited by 2 | Viewed by 1197

Abstract

This paper proposes a multi-hider dual-image reversible data-hiding algorithm. Generating dual stego images, the proposed algorithm provides a high embedding capacity, exhibits high image quality, offers reversibility to restore the stego images, and suggests seven levels of secret message extraction. The message embedding in our algorithm contains two phases. In Phase-1, we embed an n-ary secret message vector followed by an m-ary secret message in each pixel using two distinct secret keys when rendering a new image from the source and target images using an optimal weighted color-transfer process. This phase produces a tentative stego image which exhibits a new color appearance, different from the input source image. In Phase-2, we introduce a weighted modulus operation to embed a k-ary secret message vector into a dual-pixel constructed from the tentative stego image. The message concealment is elaborately designed so that the hidden secret messages are intact. This phase produces dual stego images which carry three distinct secret messages. Using legitimate secret keys, an authorized receiver can extract one or parts of secret messages and recover the tentative stego color-transferred image without arousing any suspicion. The experimental results and analysis confirm that our scheme can resist RS and PVD steganalytic attacks. In addition, our algorithm provides both high embedding capacity and better image quality, outperforming its counterparts. To the best of our knowledge, our scheme is the first in the relevant literature that provides multi-hider reversible data hiding, thereby offering various levels of message extraction for secure data communication. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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16 pages, 4012 KiB

Open AccessArticle

Image Watermarking Based Data Hiding by Discrete Wavelet Transform Quantization Model with Convolutional Generative Adversarial Architectures

by C. Annadurai, I. Nelson, K. Nirmala Devi, R. Manikandan and Amir H. Gandomi

Appl. Sci. 2023, 13(2), 804; https://doi.org/10.3390/app13020804 - 6 Jan 2023

Cited by 4 | Viewed by 1874

Abstract

Traditional watermarking methods can remove a watermark from an image, making it possible to see the copyright information about the image owner or to estimate similarities using techniques such as bit error rate and normalized correlation. Deep learning is another examination field in AI, and is utilized to develop a deep network to extract objective elements and afterwards distinguish the general environment. To assure the robustness and security of computerized image watermarking, we propose a novel algorithm using convolutional generative adversarial neural networks. This research proposed a novel technique in digital watermarking, with data hiding based on segmentation and classification, using deep learning techniques. The used input images are medical images, including Magnetic Resonance Images (MRI) and Computed Tomography (CT) images, which have been processed for noise removal, smoothening and normalization. The processed image has been watermarked using the Singular Value Decomposition-based discrete wavelet transform quantization model, being segmented and classified using convolutional generative adversarial neural networks. The experimental analysis has been carried out in terms of bit error rate, Structural Similarity Index Measure (SSIM), Normalized Cross-Correlation (NCC), training accuracy, and validation accuracy. This achieved an attained bit error rate of 71%, an SSIM of 56%, a Normalized Cross-Correlation of 71%, a training accuracy of 98%, and a validation accuracy of 95%. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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25 pages, 8746 KiB

Open AccessFeature PaperArticle

XtoE: A Novel Constructive and Camouflaged Adaptive Data Hiding and Image Encryption Scheme for High Dynamic Range Images

by Chi-Feng Lan, Chung-Ming Wang and Woei Lin

Appl. Sci. 2022, 12(24), 12856; https://doi.org/10.3390/app122412856 - 14 Dec 2022

Cited by 3 | Viewed by 1085

Abstract

High dynamic range (HDR) image data hiding and encryption has attracted much interest in recent years due the benefits of providing high quality realistic images and versatile applications, such as copyright protection, data integrity, and covert communication. In this paper, we propose a novel constructive and camouflaged adaptive data hiding and image encryption scheme for HDR images. Our algorithm disguises hidden messages when converting an original OpenEXR format to the RGBE encoding, which contains the Red, Green, and Blue color channels and an exponent E channel. During the conversion process, we determine an optimal base for each pixel by considering the user’s demands and the exponent E channel information to achieve adaptive message concealment. To prevent inappropriate access to the stego image, we perform the bit-level permutation and confusion using a 2D Sine Logistic modulation map with hyperchaotic behavior and a random permutation scheme with the time complexity of

O (N) .

To the best of our knowledge, our algorithm is the first in HDR data hiding literature able to predict the image distortion and satisfy a user’s request for the embedding capacity. Our algorithm offers 18% to 32% larger embedding rate than that provided by the current state-of-the-art works without degrading the quality of the stego image. Experimental results confirm that our scheme provides high security superior to the competitors. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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21 pages, 1641 KiB

Open AccessArticle

Advanced Dipper-Throated Meta-Heuristic Optimization Algorithm for Digital Image Watermarking

by El-Sayed M. El-Kenawy, Nima Khodadadi, Ashin Khoshnaw, Seyedali Mirjalili, Amel Ali Alhussan, Doaa Sami Khafaga, Abdelhameed Ibrahim and Abdelaziz A. Abdelhamid

Appl. Sci. 2022, 12(20), 10642; https://doi.org/10.3390/app122010642 - 21 Oct 2022

Cited by 9 | Viewed by 1842

Abstract

Recently, piracy and copyright violations of digital content have become major concerns as computer science has advanced. In order to prevent unauthorized usage of content, digital watermarking is usually employed. This work proposes a new approach to digital image watermarking that makes use of the discrete cosine transform (DCT), discrete wavelet transform (DWT), dipper-throated optimization (DTO), and stochastic fractal search (SFS) algorithms. The proposed approach involves computing the discrete wavelet transform (DWT) on the cover image to extract its sub-components, followed by the performance of a discrete cosine transform (DCT) to convert these sub-components into the frequency domain. Finding the best scale factor for watermarking is a significant challenge in most watermarking methods. The authors used an advanced optimization algorithm, which is referred to as DTOSFS, to determine the best two parameters—namely, the scaling factor and embedding coefficient—to be used while inserting a watermark into a cover image. Using the optimal values of these parameters, a watermark image can be inserted into a cover image more efficiently. The suggested approach is evaluated in comparison with the current gold standard. The normalized cross-correlation (NCC), peak-signal-to-noise ratio (PSNR), and image fidelity (IF) are used to measure the success of the proposed approach. In addition, a statistical analysis is performed to evaluate the significance and superiority of the proposed approach. The experimental results confirm the effectiveness of the proposed approach in improving upon standard watermarking methods based on the DWT and DCT. Moreover, a set of attacks is considered to study the robustness of the proposed approach, and the results confirm the expected outcomes. It is shown by the achieved results that the proposed approach can be utilized for practical digital image watermarking, and that it significantly outperforms other digital image watermarking methods. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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18 pages, 8389 KiB

Open AccessArticle

A Reversible Data-Hiding Method with Prediction-Error Expansion in Compressible Encrypted Images

by Ryota Motomura, Shoko Imaizumi and Hitoshi Kiya

Appl. Sci. 2022, 12(19), 9418; https://doi.org/10.3390/app12199418 - 20 Sep 2022

Cited by 9 | Viewed by 1596

Abstract

This paper proposes a novel reversible data-hiding method in encrypted images to achieve both a high hiding capacity and good compression performance. The proposed method can also decrypt marked encrypted images without data extraction, so marked images containing a payload can be derived from marked encrypted images. A perceptual encryption algorithm proposed for an encryption-then-compression framework is used to generate compressible encrypted images. In addition, a predictor with high accuracy and a prediction-error expansion and histogram shifting method are used for data hiding. Consequently, the proposed method can compress marked encrypted images without loss using image coding standards and achieve a high hiding rate. Experimental results show the effectiveness of the method in terms of hiding capacity or marked-image quality and lossless compression efficiency. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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13 pages, 3315 KiB

Open AccessArticle

Digital Watermarking System for Copyright Protection and Authentication of Images Using Cryptographic Techniques

by Prasanth Vaidya Sanivarapu, Kandala N. V. P. S. Rajesh, Khalid M. Hosny and Mostafa M. Fouda

Appl. Sci. 2022, 12(17), 8724; https://doi.org/10.3390/app12178724 - 31 Aug 2022

Cited by 15 | Viewed by 3294

Abstract

Digital images are transferred with ease through the network. Many users are using the images without the knowledge of the owners. Therefore, a novel watermarking scheme is proposed to ensure copyright protection and authentication of images using cryptography techniques. Here, a quick response (QR) image is generated for a watermark image that contains public and private keys prepared using a cryptosystem. Later, this QR image is scrambled using a chaotic logistic map. The public and private keys are used to cipher and decipher the data. Next, the scrambled QR watermark is embedded into a color image using a single-level discrete wavelet transform followed by singular value decomposition using the key value. Finally, the inverse process is applied to extract the watermark. The proposed method is validated using various image processing attacks. The results are then compared with state-of-the-art watermarking schemes. The experimental results show that the scheme provides good results in terms of robustness and imperceptibility. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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14 pages, 1497 KiB

Open AccessArticle

Evaluation of a Framework for Robust Image Reversible Watermarking

by Jose Juan Garcia-Hernandez, Claudia Feregrino-Uribe, Alejandra Menendez-Ortiz and Dan Williams Robledo-Cruz

Appl. Sci. 2022, 12(14), 7242; https://doi.org/10.3390/app12147242 - 18 Jul 2022

Cited by 1 | Viewed by 1217

Abstract

In the literature, robust reversible watermarking schemes (RWSs) allow the extraction of watermarks after the images have suffered attacks; however, the modified images are compromised. On the other hand, self-recovery schemes will restore the compromised regions of the images, but no secret messages are inserted in these schemes. A framework for robust reversible watermarking with signal restoration capabilities was previously proposed in the literature. This study selects four fragile reversible watermarking techniques and two self-recovery schemes to design different framework configurations. These configurations are evaluated to test the framework’s performance and determine the structure that yields better results in terms of perceptual transparency using a well-known image database as the signal input. It was found that fragile reversible watermarking schemes hold low perceptual distortion, while self-recovery schemes produce high perceptual distortion levels. The inherent characteristics of each algorithm determine, a priori, the behavior of the framework, which is approximated by a proposed equation. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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19 pages, 455 KiB

Open AccessArticle

Blockchain and Cloud to Overcome the Problems of Buyer and Seller Watermarking Protocols

by Franco Frattolillo

Appl. Sci. 2021, 11(24), 12028; https://doi.org/10.3390/app112412028 - 17 Dec 2021

Cited by 4 | Viewed by 1745

Abstract

Copyright protection of digital content has become a problem not only for web content providers but also for ordinary web users who like to publish their digital contents on social or user generated content platforms. Among the possible solutions to such a problem, digital watermarking, in conjunction with watermarking protocols, appears to be a valid alternative to current DRM (digital rights management) systems. In fact, watermarking based solutions insert perceptually invisible copyright information into the copies of contents published or distributed on the web in order to track them. Such insertions are carried out according to the watermarking protocols, which have evolved over the years from the classic “buyer and seller” paradigm into a simpler and versatile “buyer friendly” and “mediated” approach. However, such an approach cannot exploit the new technologies that characterize the current Internet. This paper presents a new watermarking protocol able to adapt the “buyer friendly” and “mediated” approach to the use of innovative technologies such as cloud platforms and blockchain. In this way, (1) content providers and common web users can take advantage of the computing and storage resources made available by cloud platforms; (2) the involvement of trusted third parties in the protocols can be reduced by using blockchain without complicating the protection scheme. In fact, these two goals make the protocol particularly suited for the current Internet. Full article

(This article belongs to the Special Issue Data Hiding and Its Applications: Digital Watermarking and Steganography (Volume II))

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