Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

Combined DWT-DISB based image watermarking optimized for decision making problems

Currently, the protection of digital information, especially in the form of multimedia information such as images, video, text, and audio. The digital nature of the multimedia data has made it prone to misuse and attack, such as is of duplication, transformation, modification, and diffusion. In this sense, it is significant to create a system for protecting the intellectual property rights of the multimedia content. The system should guarantee copyright protection, authentication, and protection against duplication of the material. The drastic development in network multimedia system has made the development of these protection systems challenging. Numerous researches have proposed the use of watermarking to address these issues. The watermarking technique obscures vital information in the original multimedia data in which the hidden data is utilized for copyright protection and authentication. The primary need for any watermarking system should be to guarantee robustness against imminent attack while retaining the quality of the watermark images. This research presents a robust image watermarking technique used to hide details of the RGB Color elements. The proposed approach is an integration of the discrete wavelet transform (DWT) and the relatively new dual intermediate significant bit (DISB). The performance evaluation of the proposed approach produced quality watermarked images that are robust. The proposed method has a PSNR of 101.97 and an NCC of 0.9780 which compare considerable well with the individual techniques

Digital Image Watermarking, Analysis of Current Methods

The rapid evolution in data transmission by the wide use of the internet, as provided an urgent need to prevent penetration and maintain the confidentiality of this data through the applying of some techniques to hide data within the carrier for example, text, image, audio and Video.A variety of image watermarking techniques have been published in the last few years which attempts to develop techniques and methods which are used to obtain better results through the fact that the changes that took place after the concealment is visible to the human eye. Digital image watermarking is one of the general information hiding problem. This study is to highlight some of these studies and analysis for use in future research and development to get to the best results

An improvement of RGB color image watermarking technique using ISB stream bit and Hadamard matrix

In the past half century, the advancement of internet technology has been rapid and widespread. The innovation provides an efficient platform for human communication and other digital applications. Nowadays, everyone can easily access, copy, modify and distribute digital contents for personal or commercial gains. Therefore, a good copyright protection is required to discourage the illicit activities. On way is to watermark the assets by embedding an owner's identity which could later on be used for authentication. Thus far, many watermarking techniques have been proposed which focus on improving three standard measures, visual quality or imperceptibility, robustness and capacity. Although their performances are encouraging, there are still plenty of rooms for improvements. Thus, this study proposes a new watermarking technique using Least Significant Bit (LSB) insertion approach coupled with Hadamard matrix. The technique involves four main stages: Firstly, the cover image is decomposed into three separate channels, Red, Green and Blue. Secondly, the Blue channel is chosen and converted into an eight bit stream. Thirdly, the second least signification bit is selected from the bit stream for embedding. In order to increase the imperceptibility a Hadamard matrix is used to find the best pixels of the cover image for the embedding task. Experimental results on standard dataset have revealed that average PSNR value is greater than 58db, which indicates the watermarked image is visually identical to its original. However, the proposed technique suffers from Gaussian and Poisson noise attacks

Optimization of medical image steganography using n-decomposition genetic algorithm

Protecting patients' confidential information is a critical concern in medical image steganography. The Least Significant Bits (LSB) technique has been widely used for secure communication. However, it is susceptible to imperceptibility and security risks due to the direct manipulation of pixels, and ASCII patterns present limitations. Consequently, sensitive medical information is subject to loss or alteration. Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. The proposed technique showed resistance to statistical analysis evaluated using Reversible Statistical (RS) analysis and histogram. It also demonstrated its superiority in imperceptibility and security measured by MSE and PSNR to Chest and Retina datasets (0.0557, 0.0550) and (60.6696, 60.7287), respectively. Still, compared to the results obtained by the proposed technique, the benchmark outperforms the Brain dataset due to the homogeneous nature of the images and the extensive black background. This research has contributed to genetic-based decomposition in medical image steganography and provides a technique that offers improved security without compromising efficiency and convergence. However, further validation is required to determine its effectiveness in real-world applications

Are Social Networks Watermarking Us or Are We (Unawarely) Watermarking Ourself?

In the last decade, Social Networks (SNs) have deeply changed many aspects of society, and one of the most widespread behaviours is the sharing of pictures. However, malicious users often exploit shared pictures to create fake profiles leading to the growth of cybercrime. Thus, keeping in mind this scenario, authorship attribution and verification through image watermarking techniques are becoming more and more important. In this paper, firstly, we investigate how 13 most popular SNs treat the uploaded pictures, in order to identify a possible implementation of image watermarking techniques by respective SNs. Secondly, on these 13 SNs, we test the robustness of several image watermarking algorithms. Finally, we verify whether a method based on the Photo-Response Non-Uniformity (PRNU) technique can be successfully used as a watermarking approach for authorship attribution and verification of pictures on SNs. The proposed method is robust enough in spite of the fact that the pictures get downgraded during the uploading process by SNs. The results of our analysis on a real dataset of 8,400 pictures show that the proposed method is more effective than other watermarking techniques and can help to address serious questions about privacy and security on SNs.Comment: 43 pages, 6 figure

Are Social Networks Watermarking Us or Are We (Unawarely) Watermarking Ourself?

In the last decade, Social Networks (SNs) have deeply changed many aspects of society, and one of the most widespread behaviours is the sharing of pictures. However, malicious users often exploit shared pictures to create fake profiles, leading to the growth of cybercrime. Thus, keeping in mind this scenario, authorship attribution and verification through image watermarking techniques are becoming more and more important. In this paper, we firstly investigate how thirteen of the most popular SNs treat uploaded pictures in order to identify a possible implementation of image watermarking techniques by respective SNs. Second, we test the robustness of several image watermarking algorithms on these thirteen SNs. Finally, we verify whether a method based on the Photo-Response Non-Uniformity (PRNU) technique, which is usually used in digital forensic or image forgery detection activities, can be successfully used as a watermarking approach for authorship attribution and verification of pictures on SNs. The proposed method is sufficiently robust, in spite of the fact that pictures are often downgraded during the process of uploading to the SNs. Moreover, in comparison to conventional watermarking methods the proposed method can successfully pass through different SNs, solving related problems such as profile linking and fake profile detection. The results of our analysis on a real dataset of 8400 pictures show that the proposed method is more effective than other watermarking techniques and can help to address serious questions about privacy and security on SNs. Moreover, the proposed method paves the way for the definition of multi-factor online authentication mechanisms based on robust digital features

A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges

The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an investigation of information security techniques in medical imaging, focusing on security goals. Encrypting a message before hiding them gives an extra layer of security, and thus, will provide an excellent solution to protect the sensitive information of patients during the sharing of medical information. Medical image steganography is a special case of image steganography, while Digital Imaging and Communications in Medicine (DICOM) is the backbone of all medical imaging divisions, whereby it is most broadly used to store and transmit medical images. The main objective of this study is to provide a general idea of what Least Significant Bit-based (LSB) steganography techniques have achieved in medical images

Reversible and imperceptible watermarking approach for ensuring the integrity and authenticity of brain MR images

The digital medical workflow has many circumstances in which the image data can be manipulated both within the secured Hospital Information Systems (HIS) and outside, as images are viewed, extracted and exchanged. This potentially grows ethical and legal concerns regarding modifying images details that are crucial in medical examinations. Digital watermarking is recognised as a robust technique for enhancing trust within medical imaging by detecting alterations applied to medical images. Despite its efficiency, digital watermarking has not been widely used in medical imaging. Existing watermarking approaches often suffer from validation of their appropriateness to medical domains. Particularly, several research gaps have been identified: (i) essential requirements for the watermarking of medical images are not well defined; (ii) no standard approach can be found in the literature to evaluate the imperceptibility of watermarked images; and (iii) no study has been conducted before to test digital watermarking in a medical imaging workflow. This research aims to investigate digital watermarking to designing, analysing and applying it to medical images to confirm manipulations can be detected and tracked. In addressing these gaps, a number of original contributions have been presented. A new reversible and imperceptible watermarking approach is presented to detect manipulations of brain Magnetic Resonance (MR) images based on Difference Expansion (DE) technique. Experimental results show that the proposed method, whilst fully reversible, can also realise a watermarked image with low degradation for reasonable and controllable embedding capacity. This is fulfilled by encoding the data into smooth regions (blocks that have least differences between their pixels values) inside the Region of Interest (ROI) part of medical images and also through the elimination of the large location map (location of pixels used for encoding the data) required at extraction to retrieve the encoded data. This compares favourably to outcomes reported under current state-of-art techniques in terms of visual image quality of watermarked images. This was also evaluated through conducting a novel visual assessment based on relative Visual Grading Analysis (relative VGA) to define a perceptual threshold in which modifications become noticeable to radiographers. The proposed approach is then integrated into medical systems to verify its validity and applicability in a real application scenario of medical imaging where medical images are generated, exchanged and archived. This enhanced security measure, therefore, enables the detection of image manipulations, by an imperceptible and reversible watermarking approach, that may establish increased trust in the digital medical imaging workflow