Digital Watermarking Technique Research Articles

An Efficient Hybrid Algorithm to Enhance Cloud Data Security with Digital Watermarking Technique

An Efficient Hybrid Algorithm to Enhance Cloud Data Security with Digital Watermarking Technique

Hybrid watermarking and encryption techniques for securing three-dimensional information

A hybrid digital watermarking and encryption technique based on the Computer Generated Holography (CGH) and fractional Fourier transform (FRFT) combined with singular value decomposition (SVD) algorithm is proposed for securing three-dimensional (3D) information. Initially, hierarchical 3D information is encrypted using the angular spectrum diffraction method and a random phase key. This process yields a binary real valued CGH, where incorporating a random phase key broadens the key space and adds complexity, effectively scrambling and concealing the 3D information. Subsequently, the encrypted binary real valued CGH is embedded into the host image as a watermark using the FRFT-SVD algorithm. This hybrid approach enhances the security of the watermarking process. In the final step, the CGH watermark is extracted using the inverse operation of the embedding algorithm. Applying the correct optical key and angular spectrum inverse algorithm successfully reconstructs the 3D information. The watermark algorithm’s efficiency significantly improves by leveraging the rapid computational speed and high focusing capabilities of the FRFT. Additionally, integrating SVD enhances the image’s resistance to geometric attacks, thereby improving the algorithm’s invisibility and robustness. The proposed scheme effectively achieves the encryption and digital watermarking of 3D information. Simulation results substantiate the presented watermarking scheme’s efficacy and robustness.

A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction

A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction

Techniques for Digital Watermarking in Images: A Review

Techniques for Digital Watermarking in Images: A Review

Optimized and secure digital image watermarking technique using Henon mapping in redundant domain

Optimized and secure digital image watermarking technique using Henon mapping in redundant domain

A review of digital watermarking techniques: Current trends, challenges and opportunities

The rapid progress in the transfer of information and its availability are the reasons behind the widespread use of the Internet. Document images are the most complicated and challenging category among various forms of digital data to which watermarking can be applied for its security and authentication. Watermarking of the document image is a very difficult task, since these images have very limited redundancy. Because of this factor there has been very little research in this area. A comprehensive research should be carried out to ensure the effective assessment, review as well as implementation of document image watermarking techniques. This paper reviews the existing document image watermarking by considering different evaluation parameters. Based on this review, a variety of challenges and directions have been prescribed for the development of effective watermarking techniques for document images.

Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition for Enhanced Imperceptibility and Robustness

Digital multimedia elements such as text, image, audio, and video can be easily manipulated because of the rapid rise of multimedia technology, making data protection a prime concern. Hence, copyright protection, content authentication, and integrity verification are today’s new challenging issues. To address these issues, digital image watermarking techniques have been proposed by several researchers. Image watermarking can be conducted through several transformations, such as discrete wavelet transform (DWT), singular value decomposition (SVD), orthogonal matrix Q and upper triangular matrix R (QR) decomposition, and non-subsampled contourlet transform (NSCT). However, a single transformation cannot simultaneously satisfy all the design requirements of image watermarking, which makes a platform to design a hybrid invisible image watermarking technique in this work. The proposed work combines four-level (4L) DWT and two-level (2L) SVD. The Arnold map initially encrypts the watermark image, and 2L SVD is applied to it to extract the s components of the watermark image. A 4L DWT is applied to the host image to extract the LL sub-band, and then 2L SVD is applied to extract s components that are embedded into the host image to generate the watermarked image. The dynamic-sized watermark maintains a balanced visual impact and non-blind watermarking preserves the quality and integrity of the host image. We have evaluated the performance after applying several intentional and unintentional attacks and found high imperceptibility and improved robustness with enhanced security to the system than existing state-of-the-art methods.

Data Hiding With Deep Learning: A Survey Unifying Digital Watermarking and Steganography

The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding. By embedding information into a noise-tolerant signal, such as audio, video, or images, digital watermarking and steganography techniques can be used to protect sensitive intellectual property (IP) and enable confidential communication, ensuring that the information embedded is only accessible to authorized parties. This survey provides an overview of recent developments in deep learning techniques deployed for data hiding, categorized systematically according to model architectures and noise injection methods. In addition, potential future research directions that unite digital watermarking and steganography on software engineering to enhance security and mitigate risks are suggested and deliberated. This contribution furthers the creation of a more trustworthy digital world and advances responsible artificial intelligence (AI).

Semi-Blind watermarking using convolutional attention-based turtle shell matrix for tamper detection and recovery of medical images

“Telemedicine or e-medicine” refers to an electronic communication system that shares medical information from one location to another through the transmission channel. The increase in multimedia data sharing/transmission across the communication channel has raised to an uncontrollable stage. Thus, the transmission of medical reports across the network has increased higher, which has a chance of tampering either intentional or unintentional attacks. In the case of deliberate attacks, tamper detection and localization are the highly required criteria to verify the originality. In such cases, medical image authentication, security, and integrity verification are also essential criteria in telemedicine applications to verify whether the report belongs to the right person or not. To achieve these criteria and to satisfy these requirements Digital watermarking techniques are highly suggested. Much research has been carried out to address this issue, but some drawbacks and limitations still need to be addressed. The objective is to accomplish a Tamper detection, localization, and recovery (TDLR) system with minimal source information at the receiver end with a better payload or embedding capacity. This paper presents a novel Conventional Attention network (CoAtNet) based invariant watermark generation. A two-level embedding is proposed to enhance watermark security, where image tamper localization and recovery information is generated. The primary level of embedding is carried out by the Turtle Shell Data Hiding Algorithm (TSDH), and the secondary level of embedding is carried out by the DWT-SVD transform. The result shows that the proposed model achieves high imperceptibility and tamper detection accuracy of 60.24 and 99.51% respectively. Furthermore, the suggested system performed well in evaluations of tamper detection and image restoration for various malicious attacks against state-of-the-art systems.

Selection of Digital Watermarking Techniques for Medical Image Security by Using the Fuzzy Analytical Hierarchy Process

Background: The watermarking technique is a security algorithm for medical images and the patient's information. Watermarking is used for maintaining the robustness, integrity, confidentiality, authentication, and complexity of medical images. Objective: The selection of medical image watermarking technique is multi-criteria decision-making and an automatic way of algorithm selection for security and privacy. However, it is difficult to select a better watermarking technique through traditional selection techniques. Methods: To deal with this problem, a multicriteria-based fuzzy analytic hierarchy process (FAHP) was proposed. This method is applied for algorithm selection for the security of medical images in healthcare. In this method, we first determined the list of criteria and alternatives, which directly affect the decision of the medical image security algorithm. Then, the proposed method was applied to the criteria and alternatives. Results: We provided the rank according to the obtained weights of the algorithm. Furthermore, the overall results and ranking of the algorithms were also presented in this article. Conclusion: Integrity was found to have the highest weight (0.509) compared to the other criteria. The weight of the other criteria, namely authentication, was 0.165, robustness was 0.151, confidentiality was 0.135, and complexity was 0.038. Thus, in terms of ranking, integrity was reported to be of the highest priority among the five criteria attributes.

A secure fractional-order polar harmonic transforms based image watermarking scheme using funk singular value decomposition

In addition to existing cryptographic systems, watermarking technologies have been developed to add extra security. Digital watermarking utilizes embedding or hiding techniques to protect multimedia files from copyright violations. Fundamental procedures of digital watermarking techniques are embedding and extraction. Singular value decomposition (SVD) based Image watermarking schemes become popular owing to its better trade-off among robustness and imperceptibility. Nevertheless, false positive problem (FPP) is a major issue of SVD-based watermarking schemes. The singular value that is a fixed value and does not contain structural information about image is the primary cause of FPP problem. Therefore, Message Digest algorithm image watermarking scheme based on Funk Singular Value Decomposition and Fractional-Order Polar Harmonic Transform (FSVD-FOPHT) is proposed in this paper to address this problem. The MD-5 algorithm is used to extract data from the host and watermark imageries and then create secret key. The FSVD-FOPHT method is utilized to hide watermark information in host image. The secret keys are extracted from hided image using inverse process of Fractional-Order Polar Harmonic Transforms with Funk Singular Value Decomposition algorithm. By using the extraction procedure, watermark image is extracted, and then reconstructs original watermarked image. During extraction procedure, the secret key is used for authentication to address FPP. Then, the proposed method is implemented in MATLAB and performance is analyzed with evaluation metrics, such as Embedding capacity, MSE, PSNR, and NC. The proposed method provide 14.6%, 17.34%, 19.53%, 21.46% and 23.89% high PSNR for cold-snow-landscape-water test image, 14.29%, 16.47%, 18.39%, 20.16% and 21.93% high PSNR for landscape-nature-sky-blue Test image, 16.85%, 19.99%, 22.70%, 27.22% and 29.16% high Embedding Capacity for cold-snow-landscape-water test image 22.83%, 24.64%, 27.92%, 29.60% and 31.77% high Embedding Capacity for landscape-nature-sky-blue Test image 35.38%, 32.63%, 30.95%, 28.61% and 26.08% low extraction time compared with existing methods SVD-CMSF-SIW, FE-IWS-DNN, AR-IWS-DNN, BBET-SHA1-SIW and LSB-DWT-SIW respectively.

A Review of Digital Watermarking Approaches for Forensic Applications

Abstract: There has been remarkable growth in the digital domain. This has led to the production of a huge amount of digital data in the form of text messages, documents, audio/speech signals, digital images, videos, etc. In forensics, digital information (i.e., images of crime scenes, etc.) is very important to examine cases and collect the proof regarding the incident. This further leads to judge the victims and culprits by the court for appropriate actions. So, even a slight change (intentional/ unintentional) may lead to the wrong judgement. Several digital signal processing tools are easily available to process this type of digital data, which means data may get disrupted, altered, or deform in such a way that the authenticity gets compromised. In such cases, it can be difficult to recognize the source information as well as to check the originality/intactness of the digital data. In the recent past, several techniques have come into existence to protect digital data against security issues. Steganography, cryptography, and watermarking are examples of security techniques, which have been widely used for data security and forensic applications for a long time. Specifically, digital watermarking techniques provide many useful features to help users regarding data security and authentication without affecting other data characteristics. This work is an attempt to provide a review of recent digital image watermarking approaches for forensic applications.

Watermarking in Medical Image

Medical image security is possible using digital watermarking techniques. Important information is included in a host medical image in order to provide integrity, consistency, and authentication in the healthcare information system. This paper introduces a proposed method for embedding invisible watermarking in the 3D medical image. The cover medical image used is DICOM which consists of a number of slices, each one representing a sense, firstly must separate the ROI (Region of Interest) and NROI (Not Region Of Interest) for each slice, the separation process performed by the particular person who selected by hand the ROI. The embedding process is based on a key generated from Arnold's chaotic map used as the position of a pixel in the slices with the highest saturation for embedding a secret message in the NROI because the ROI contains the information of the ill, so it cannot be modified. The evaluation of the proposed method using PSNR and MSE shows good results according to both requirements of the watermark system, the invisibility and quality of the watermarked medical image where the PSNR value is up to 43.3936 and MSE is up to 0.000041.

A robust semi-fragile watermarking system using Pseudo-Zernike moments and dual tree complex wavelet transform for social media content authentication.

With the growing use of mobile devices and Online Social Networks (OSNs), sharing digital content, especially digital images is extremely high as well as popular. This made us convenient to handle the ongoing COVID-19 crisis which has brought about years of change in the sharing of digital content online. On the other hand, the digital image processing tools which are powerful enough to make the perfect image duplication compromises the privacy of the transmitted digital content. Therefore, content authentication, proof of ownership, and integrity of digital images are considered crucial problems in the world of digital that can be accomplished by employing a digital watermarking technique. On contrary, watermarking issues are to triumph trade-offs among imperceptibility, robustness, and payload. However, most existing systems are unable to handle the problem of tamper detection and recovery in case of intentional and unintentional attacks concerning these trade-offs. Also, the existing system fails to withstand the geometrical attacks. To resolve the above shortcomings, this proposed work offers a new multi-biometric based semi-fragile watermarking system using Dual-Tree Complex Wavelet Transform (DTCWT) and pseudo-Zernike moments (PZM) for content authentication of social media data. In this research work, the DTCWT-based coefficients are used for achieving maximum embedding capacity. The Rotation and noise invariance properties of Pseudo Zernike moments make the system attain the highest level of robustness when compared to conventional watermarking systems. To achieve authentication and proof of identity, the watermarks of about four numbers are used for embedding as a replacement for a single watermark image in traditional systems. Among four watermarks, three are the biometric images namely Logo or unique image of the user, fingerprint biometric of the owner, and the metadata of the original media to be transmitted. In addition, to achieve the tamper localization property, the Pseudo Zernike moments of the original cover image are obtained as a feature vector and also embedded as a watermark. To attain a better level of security, each watermark is converted into Zernike moments, Arnold scrambled image, and SHA outputs respectively. Then, to sustain the trade-off among the watermarking parameters, the optimal embedding location is determined. Moreover, the watermarked image is also signed by the owner's other biometric namely digital signature, and converted into Public key matrix Pkm and embedded onto the higher frequency subband namely, HL of the 1-level DWT. The proposed system also accomplishes a multi-level authentication, among that the first level is attained by the decryption of the extracted multiple watermark images with the help of the appropriate decryption mechanism which is followed by the comparison of the authentication key which is extracted using the key which is regenerated at the receiver's end. The simulation outcomes evident that the proposed system shows superior performance towards content authentication, to most remarkable intentional and unintentional attacks among the existing watermarking systems.

Hybrid and Invisible Digital Image Watermarking Technique Using IWT-DCT and Hopfield Neural Network

According to the characteristic of HVS (Human Visual System) and the association memory ability of the neural network, an adaptive image watermarking algorithm based on a neural network is proposed invisible image watermarking is a secret embedding scheme for hiding secret images into a cover image file and the purpose of invisible watermarking is copyrights protection. Wavelet transformation-based image watermarking techniques provide better robustness for statistical attacks in comparison to Discrete Cosine Transform domain-based image watermarking. The joined method of IWT (Integer Wavelet Transform) and DCT (Discrete Cosine Transform) gives benefits to the two procedures. The IWT has an impediment of portion misfortune in embedding which increments the mean square estimate as SIM and results in diminishing PSNR. The capacity of drawing in is improved by pretreatment and re-treatment of image scrambling and Hopfield neural network. The proposed algorithm presents a hybrid integer wavelet transform and discrete cosine transform-based watermarking technique to obtain increased imperceptibility and robustness compared to the IWT-DCT-based watermarking technique. The proposed watermarking technique reduces the fractional loss compared to DWT-based watermarking.

BacterialWmark: telemedicine watermarking technique using bacterial foraging for smart healthcare system

A transform domain digital image watermarking technique is proposed using bacterial foraging optimization (BFO) for telemedicine applications. To make a trade-off between robustness, imperceptibility, and authenticity is a significant focus of our work. The field of telemedicine is one of the critical areas for an intruder to make unwanted changes. The size of medical data is exponentially increasing since the pandemic. So, the security of medical data is also a big concern. One of the most important techniques to safeguard medical data is image watermarking. The digital imaging and communications in medical images of liver ultrasound are taken as input host images. Peak signal-to-noise ratio, Kullback–Leibler distance, and root-mean-square difference are used for BFO. The proposed BacterialWmark technique shows a significant improvement in robustness and imperceptibility compared with other existing techniques. The computational complexity of the proposed work is also less. The authentication of the watermarked image is successfully executed as the features are perfectly matched with the aid of the MinEigen algorithm. So, the BacterialWmark algorithm can be used in the field of telemedicine efficiently.

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

Image Watermarking Using Least Significant Bit and Canny Edge Detection.

With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today's world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB's high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks.

An enhanced digital image watermarking technique using DWT-HD-SVD and deep convolutional neural network

An enhanced digital image watermarking technique using DWT-HD-SVD and deep convolutional neural network

Digital image watermarking technique based on adaptive median filter and HL sub-band of two-stage DWT

Digital image watermarking technique based on adaptive median filter and HL sub-band of two-stage DWT