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Entropy Based Data Hiding and Its Applications

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 16355

Special Issue Editors

Department of Information Management, Chaoyang University of Technology, Taichung 41349, Taiwan
Interests: information hiding; steganography; image processing; interactive game design; 3D modeling
Special Issues, Collections and Topics in MDPI journals
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
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Data hiding techniques have been widely used in many human-centric applications, for example, secret sharing, tempered detection and recovery, copyright protection, data integrity, covert communication, authentication, and so on. In a hiding scheme, multimedia content such as text, audio, image, video, and compressed code could be used as the cover media to carry the secret message or watermark for generating the stegomedia. Data hiding techniques become more and more important in providing multimedia security.

Researchers have proposed a lot of state-of-the-art hiding schemes. Many of the schemes attempt to find optimal performance by applying concepts of information theory or entropy. These kinds of schemes adopt entropy theory to find proper places to modify the pixel or coefficient for concealing the secret message into the cover media.

The goal of this Special Issue is to concentrate on (but not limited to) the improvement of data hiding algorithms through information entropy, and on the application of entropy in real-world data hiding techniques. It will bring together researchers and practitioners from different research fields including data hiding, signal processing, cryptography or information theory, among others, to contribute with original research outcomes that address issues in data hiding algorithms using information theory approaches.

Keywords

  • steganography
  • digital watermarking
  • information hiding
  • coverless data hiding
  • reversible data hiding and applications
  • ownership proof/copyright protection
  • visual cryptography
  • embedding capacity
  • signal processing
  • embedding capacity
  • emerging applications of data hiding in IoT and big data
  • extraction/detection
  • data integrity

Published Papers (8 papers)

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Research

14 pages, 1886 KiB  
Article
A Dual Blind Watermarking Method for 3D Models Based on Normal Features
Entropy 2023, 25(10), 1369; https://doi.org/10.3390/e25101369 - 22 Sep 2023
Viewed by 522
Abstract
Digital watermarking technology is an important means to effectively protect three-dimensional (3D) model data. Among them, “blind detection” and “robustness” are key and difficult points in the current research of digital watermarking technology based on 3D models. In order to realize the blind [...] Read more.
Digital watermarking technology is an important means to effectively protect three-dimensional (3D) model data. Among them, “blind detection” and “robustness” are key and difficult points in the current research of digital watermarking technology based on 3D models. In order to realize the blind detection of a watermark and improve its robustness against various common attacks at the same time, this paper proposes a dual blind watermarking method based on the normal feature of the centroid of first-ring neighboring points. The local spherical coordinate system is constructed by calculating two different normal vectors, and the first pattern watermark and the second random binary sequence watermark are embedded, respectively. The experimental results show that this method can not only realize the blind detection of dual watermarks, but also have the ability to resist common attacks such as translation, rotation, scaling, cropping, simplification, smoothing, noise, and vertex reordering to a certain extent. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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20 pages, 6578 KiB  
Article
Dynamic Information-Hiding Method with High Capacity Based on Image Interpolating and Bit Flipping
Entropy 2023, 25(5), 744; https://doi.org/10.3390/e25050744 - 01 May 2023
Viewed by 1039
Abstract
In this era of rapid information exchange in public networks, there is a risk to information security. Data hiding is an important technique for privacy protection. Image interpolation is an important data-hiding technique in image processing. This study proposed a method called neighbor [...] Read more.
In this era of rapid information exchange in public networks, there is a risk to information security. Data hiding is an important technique for privacy protection. Image interpolation is an important data-hiding technique in image processing. This study proposed a method called neighbor mean interpolation by neighboring pixels (NMINP) that calculates a cover image pixel by neighbor mean interpolation and neighboring pixels. To reduce image distortion, NMINP limits the number of bits when embedding secret data, making NMINP have a higher hiding capacity and peak signal-to-noise ratio (PSNR) than other methods. Furthermore, in some cases, the secret data are flipped, and the flipped data are treated in ones’ complement format. A location map is not needed in the proposed method. Experimental results comparing NMINP with other state-of-the-art methods show that NMINP improves the hiding capacity by more than 20% and PSNR by 8%. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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26 pages, 7359 KiB  
Article
A Multi-Directional Pixel-Swapping Approach (MPSA) for Entropy-Retained Reversible Data Hiding in Encrypted Images
Entropy 2023, 25(4), 563; https://doi.org/10.3390/e25040563 - 25 Mar 2023
Cited by 1 | Viewed by 1056
Abstract
Reversible data hiding (RDH), a promising data-hiding technique, is widely examined in domains such as medical image transmission, satellite image transmission, crime investigation, cloud computing, etc. None of the existing RDH schemes addresses a solution from a real-time aspect. A good compromise between [...] Read more.
Reversible data hiding (RDH), a promising data-hiding technique, is widely examined in domains such as medical image transmission, satellite image transmission, crime investigation, cloud computing, etc. None of the existing RDH schemes addresses a solution from a real-time aspect. A good compromise between the information embedding rate and computational time makes the scheme suitable for real-time applications. As a solution, we propose a novel RDH scheme that recovers the original image by retaining its quality and extracting the hidden data. Here, the cover image gets encrypted using a stream cipher and is partitioned into non-overlapping blocks. Secret information is inserted into the encrypted blocks of the cover image via a controlled local pixel-swapping approach to achieve a comparatively good payload. The new scheme MPSA allows the data hider to hide two bits in every encrypted block. The existing reversible data-hiding schemes modify the encrypted image pixels leading to a compromise in image security. However, the proposed work complements the support of encrypted image security by maintaining the same entropy of the encrypted image in spite of hiding the data. Experimental results illustrate the competency of the proposed work accounting for various parameters, including embedding rate and computational time. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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26 pages, 31872 KiB  
Article
Efficient Video Watermarking Algorithm Based on Convolutional Neural Networks with Entropy-Based Information Mapper
Entropy 2023, 25(2), 284; https://doi.org/10.3390/e25020284 - 02 Feb 2023
Cited by 7 | Viewed by 1606
Abstract
This paper presents a method for the transparent, robust, and highly capacitive watermarking of video signals using an information mapper. The proposed architecture is based on the use of deep neural networks to embed the watermark in the luminance channel in the YUV [...] Read more.
This paper presents a method for the transparent, robust, and highly capacitive watermarking of video signals using an information mapper. The proposed architecture is based on the use of deep neural networks to embed the watermark in the luminance channel in the YUV color space. An information mapper was used to enable the transformation of a multi-bit binary signature of varying capacitance reflecting the entropy measure of the system into a watermark embedded in the signal frame. To confirm the effectiveness of the method, tests were carried out for video frames with a resolution of 256 × 256 pixels, with a watermark capacity of 4 to 16,384 bits. Transparency metrics (SSIM and PSNR) and a robustness metric—the bit error rate (BER)—were used to assess the performance of the algorithms. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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16 pages, 10260 KiB  
Article
Reversible Data Hiding in Encrypted Image Using Multiple Data-Hiders Sharing Algorithm
Entropy 2023, 25(2), 209; https://doi.org/10.3390/e25020209 - 21 Jan 2023
Cited by 5 | Viewed by 1288
Abstract
Reversible Data Hiding in Encrypted Image (RDHEI) is a technology for embedding secret information in an encrypted image. It allows the extraction of secret information and lossless decryption and the reconstruction of the original image. This paper proposes an RDHEI technique based on [...] Read more.
Reversible Data Hiding in Encrypted Image (RDHEI) is a technology for embedding secret information in an encrypted image. It allows the extraction of secret information and lossless decryption and the reconstruction of the original image. This paper proposes an RDHEI technique based on Shamir’s Secret Sharing technique and multi-project construction technique. Our approach is to let the image owner hide the pixel values in the coefficients of the polynomial by grouping the pixels and constructing a polynomial. Then, we substitute the secret key into the polynomial through Shamir’s Secret Sharing technology. It enables the Galois Field calculation to generate the shared pixels. Finally, we divide the shared pixels into 8 bits and allocate them to the pixels of the shared image. Thus, the embedded space is vacated, and the generated shared image is hidden in the secret message. The experimental results demonstrate that our approach has a multi-hider mechanism and each shared image has a fixed embedding rate, which does not decrease as more images are shared. Additionally, the embedding rate is improved compared with the previous approach. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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23 pages, 546 KiB  
Article
Information Hiding in the DICOM Message Service and Upper Layer Service with Entropy-Based Detection
Entropy 2022, 24(2), 176; https://doi.org/10.3390/e24020176 - 25 Jan 2022
Cited by 3 | Viewed by 5214
Abstract
The DICOM (Digital Imaging and COmmunication in Medicine) standard provides a framework for a diagnostically-accurate representation, processing, transfer, storage and display of medical imaging data. Information hiding in DICOM is currently limited to the application of digital media steganography and watermarking [...] Read more.
The DICOM (Digital Imaging and COmmunication in Medicine) standard provides a framework for a diagnostically-accurate representation, processing, transfer, storage and display of medical imaging data. Information hiding in DICOM is currently limited to the application of digital media steganography and watermarking techniques on the media parts of DICOM files, as well as text steganographic techniques for embedding information in metadata of DICOM files. To improve the overall security of the DICOM standard, we investigate its susceptibility to network steganographic techniques. To this aim, we develop several network covert channels that can be created by using a specific transport mechanism – the DICOM Message Service and Upper Layer Service. The bandwidth, undetectability and robustness of the proposed covert channels are evaluated, and potential countermeasures are suggested. Moreover, a detection mechanism leveraging entropy-based metrics is introduced and its performance has been assessed. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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23 pages, 5973 KiB  
Article
Reversible Data Hiding in Encrypted Image Based on (7, 4) Hamming Code and UnitSmooth Detection
Entropy 2021, 23(7), 790; https://doi.org/10.3390/e23070790 - 22 Jun 2021
Cited by 7 | Viewed by 1880
Abstract
With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) plays the dual role of privacy protection and secret information transmission. RDHEI has a good application prospect and practical value. The current RDHEI algorithms still have room [...] Read more.
With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) plays the dual role of privacy protection and secret information transmission. RDHEI has a good application prospect and practical value. The current RDHEI algorithms still have room for improvement in terms of hiding capacity, security and separability. Based on (7, 4) Hamming Code and our proposed prediction/ detection functions, this paper proposes a Hamming Code and UnitSmooth detection based RDHEI scheme, called HUD-RDHEI scheme for short. To prove our performance, two database sets—BOWS-2 and BOSSBase—have been used in the experiments, and peak signal to noise ratio (PSNR) and pure embedding rate (ER) are served as criteria to evaluate the performance on image quality and hiding capacity. Experimental results confirm that the average pure ER with our proposed scheme is up to 2.556 bpp and 2.530 bpp under BOSSBase and BOWS-2, respectively. At the same time, security and separability is guaranteed. Moreover, there are no incorrect extracted bits during data extraction phase and the visual quality of directly decrypted image is exactly the same as the cover image. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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23 pages, 6560 KiB  
Article
Improving the Reversible LSB Matching Scheme Based on the Likelihood Re-Encoding Strategy
Entropy 2021, 23(5), 577; https://doi.org/10.3390/e23050577 - 08 May 2021
Cited by 5 | Viewed by 2117
Abstract
In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.’s scheme, there are [...] Read more.
In 2018, Tseng et al. proposed a dual-image reversible embedding method based on the modified Least Significant Bit matching (LSB matching) method. This method improved on the dual-image LSB matching method proposed by Lu et al. In Lu et al.’s scheme, there are seven situations that cannot be restored and need to be modified. Furthermore, the scheme uses two pixels to conceal four secret bits. The maximum modification of each pixel, in Lu et al.’s scheme, is two. To decrease the modification, Tseng et al. use one pixel to embed two secret bits and allow the maximum modification to decrease from two to one such that the image quality can be improved. This study enhances Tseng et al.’s method by re-encoding the modified rule table based on the probability of each hiding combination. The scheme analyzes the frequency occurrence of each combination and sets the lowest modified codes to the highest frequency case to significantly reduce the amount of modification. Experimental results show that better image quality is obtained using our method under the same amount of hiding payload. Full article
(This article belongs to the Special Issue Entropy Based Data Hiding and Its Applications)
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