Robust non-blind color video watermarking using QR decomposition and entropy analysis

Issues such as content identification, document and image security, audience measurement, ownership and copyright among others can be settled by the use of digital watermarking. Many recent video watermarking methods show drops in visual quality of the sequences. The present work addresses the aforementioned issue by introducing a robust and imperceptible non-blind color video frame watermarking algorithm. The method divides frames into moving and non-moving parts. The non-moving part of each color channel is processed separately using a block-based watermarking scheme. Blocks with an entropy lower than the average entropy of all blocks are subject to a further process for embedding the watermark image. Finally a watermarked frame is generated by adding moving parts to it. Several signal processing attacks are applied to each watermarked frame in order to perform experiments and are compared with some recent algorithms. Experimental results show that the proposed scheme is imperceptible and robust against common signal processing attacks

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks

Wavelet based digital art protection

This thesis objective is to provide a robust watermarking algorithm to protect digital images. The proposed algorithm is using wavelet-based watermarking in which we are investigating how embedding in high-frequency subbands and low-frequency subbands would affect the robustness of the watermark while facing typical signal processing attacks

AN INVESTIGATION OF DIFFERENT VIDEO WATERMARKING TECHNIQUES

Watermarking is an advanced technology that identifies to solve the problem of illegal manipulation and distribution of digital data. It is the art of hiding the copyright information into host such that the embedded data is imperceptible. The covers in the forms of digital multimedia object, namely image, audio and video. The extensive literature collected related to the performance improvement of video watermarking techniques is critically reviewed and presented in this paper. Also, comprehensive review of the literature on the evolution of various video watermarking techniques to achieve robustness and to maintain the quality of watermarked video sequences

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Robust color image watermarking using Discrete Wavelet Transform, Discrete Cosine Transform and Cat Face Transform

The primary concern in color image watermarking is to have an effective watermarking method that can be robust against common image processing attacks such as JPEG compression, rotation, sharpening, blurring, and salt and pepper attacks for copyright protection purposes. This research examined the existing color image watermarking methods to identify their strengths and weaknesses, and then proposed a new method and the best embedding place in the host image to enhance and overcome the existing gap in the color image watermarking methods. This research proposed a new robust color image watermarking method using Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Cat Face Transform. In this method, both host and watermark images decomposed into three color channels: red, green, and blue. The second level DWT was applied to each color channel of the host image. DWT decomposed the image into four sub-band coefficients: Low-pass filter in the row, Low-pass filter in the column (LL) signifies approximation coefficient, High-pass filter in the row, Low-pass filter in the column (HL) signifies horizontal coefficient, Low-pass filter in the row, High-pass filter in the column (LH) signifies vertical coefficient, and High-pass filter in the row, High-pass filter in the column (HH) signifies diagonal coefficient. Then, HL2 and LH2 were chosen as the embedding places to improve the robustness and security, and they were divided into 4×4 non-overlapping blocks, then DCT was applied on each block. DCT turned a signal into the frequency domain, which is effective in image processing, specifically in JPEG compression due to good performance. On the other hand, the Cat Face Transform method with a private key was used to enhance the robustness of the proposed method by scrambling the watermark image before embedding. Finally, the second private key was used to embed the watermark in the host image. The results show enhanced robustness against common image processing attacks: JPEG compression (3.37%), applied 2% salt and pepper (0.4%), applied 10% salt and pepper (2%), applied 1.0 radius sharpening (0.01%), applied 1.0 radius blurring (8.1%), and can withstand rotation attack. In sum, the proposed color image watermarking method indicates better robustness against common image processing attacks compared to other reviewed methods

A Watermarking Algorithm Based on DCT and JPEG Quantization Table

In this paper, we propose a scheme of watermark embedding and extracting based on DCT transform and JPEG quantization table. Firstly, the image is divided into non-overlapping 8 × 8 blocks, and each block is transformed by DCT. Then, a pair of points with the same quantization value is selected by the JPEG quantization table in order to embed one watermark bit, and the adjustment coefficients are adaptively selected by using the visual masking property of HVS. The experimental results presented in this paper showed that our proposed algorithm is robust to JPEG compression under different quality factors

Optimized DWT Based Digital Image Watermarking and Extraction Using RNN-LSTM

The rapid growth of Internet and the fast emergence of multi-media applications over the past decades have led to new problems such as illegal copying, digital plagiarism, distribution and use of copyrighted digital data. Watermarking digital data for copyright protection is a current need of the community. For embedding watermarks, robust algorithms in die media will resolve copyright infringements. Therefore, to enhance the robustness, optimization techniques and deep neural network concepts are utilized. In this paper, the optimized Discrete Wavelet Transform (DWT) is utilized for embedding the watermark. The optimization algorithm is a combination of Simulated Annealing (SA) and Tunicate Swarm Algorithm (TSA). After performing the embedding process, the extraction is processed by deep neural network concept of Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM). From the extraction process, the original image is obtained by this RNN-LSTM method. The experimental set up is carried out in the MATLAB platform. The performance metrics of PSNR, NC and SSIM are determined and compared with existing optimization and machine learning approaches. The results are achieved under various attacks to show the robustness of the proposed work

A review and open issues of diverse text watermarking techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetches more attention due to the fast growth of using the internet; it is applied for sending secret information by using different techniques. Watermarking is one of major important technique in information hiding. Watermarking is of hiding secret data into a carrier media to provide the privacy and integrity of information so that no one can recognize and detect it's accepted the sender and receiver. In watermarking, many various carrier formats can be used such as an image, video, audio, and text. The text is most popular used as a carrier files due to its frequency on the internet. There are many techniques variables for the text watermarking; each one has its own robust and susceptible points. In this study, we conducted a review of text watermarking in the spatial domain to explore the term text watermarking by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2013 to 2018. The aims of this paper are to provide an overview of text watermarking and comparison between approved studies as discussed according to the Arabic text characters, payload capacity, Imperceptibility, authentication, and embedding technique to open important research issues in the future work to obtain a robust method