Copyright Protection of Color Imaging Using Robust-Encoded Watermarking

In this paper we present a robust-encoded watermarking method applied to color images for copyright protection, which presents robustness against several geometric and signal processing distortions. Trade-off between payload, robustness and imperceptibility is a very important aspect which has to be considered when a watermark algorithm is designed. In our proposed scheme, previously to be embedded into the image, the watermark signal is encoded using a convolutional encoder, which can perform forward error correction achieving better robustness performance. Then, the embedding process is carried out through the discrete cosine transform domain (DCT) of an image using the image normalization technique to accomplish robustness against geometric and signal processing distortions. The embedded watermark coded bits are extracted and decoded using the Viterbi algorithm. In order to determine the presence or absence of the watermark into the image we compute the bit error rate (BER) between the recovered and the original watermark data sequence. The quality of the watermarked image is measured using the well-known indices: Peak Signal to Noise Ratio (PSNR), Visual Information Fidelity (VIF) and Structural Similarity Index (SSIM). The color difference between the watermarked and original images is obtained by using the Normalized Color Difference (NCD) measure. The experimental results show that the proposed method provides good performance in terms of imperceptibility and robustness. The comparison among the proposed and previously reported methods based on different techniques is also provided

A New Digital Video Watermarking Using Decimated Wavelet and Principle Component Analysis in YCbCr Domain

Digital watermarking is a technology used for security and for the copyright protection of digital media application. In this letter, we introduced “A New Digital Video Watermarking Using Decimated Wavelet and Principle Component Analysis in YCbCr domain”. First, the input video stream will be divided into number of frames and then select one frame to embed the information into it. Now convert it into YCbCr color space and apply DWT followed by PCA to get the watermarked frame then replace this frame with the original frame to obtain the watermarked video. It has also tested for various attacks such asRST, cropping, compression, filtering and Gaussian noise successfully with reduced bit error. Peak signal to noise ratio (PSNR) and structural similarity index (SSIM) used to measure the quality of watermarked frame. Simulated results had shown that the proposed algorithm gives more superior results and higher imperceptibility over existing algorithm in terms of quality metrics

Application of Stochastic Diffusion for Hiding High Fidelity Encrypted Images

Cryptography coupled with information hiding has received increased attention in recent years and has become a major research theme because of the importance of protecting encrypted information in any Electronic Data Interchange system in a way that is both discrete and covert. One of the essential limitations in any cryptography system is that the encrypted data provides an indication on its importance which arouses suspicion and makes it vulnerable to attack. Information hiding of Steganography provides a potential solution to this issue by making the data imperceptible, the security of the hidden information being a threat only if its existence is detected through Steganalysis. This paper focuses on a study methods for hiding encrypted information, specifically, methods that encrypt data before embedding in host data where the ‘data’ is in the form of a full colour digital image. Such methods provide a greater level of data security especially when the information is to be submitted over the Internet, for example, since a potential attacker needs to first detect, then extract and then decrypt the embedded data in order to recover the original information. After providing an extensive survey of the current methods available, we present a new method of encrypting and then hiding full colour images in three full colour host images with out loss of fidelity following data extraction and decryption. The application of this technique, which is based on a technique called ‘Stochastic Diffusion’ are wide ranging and include covert image information interchange, digital image authentication, video authentication, copyright protection and digital rights management of image data in general

STUDY ON AUDIO AND VIDEO WATERMARKING

This paper gives the overview of audio and video watermarking. This paper introduces the basic requirements that affect the algorithms for audio and video watermarking which are perceptibility, robustness and security. The attacks which cause manipulations of the audio and video signals are also discussed. The common group of attacks on audio and video data is dynamics, filtering, conversion, compression, noise, modulation, time stretch and pitch shift, multiple watermark, cropping, rotation etc. The applications of audio and video watermarking are Fingerprinting, copyright protection, authentication, copy control etc. The audio watermarking techniques can be classified into Time-domain and Frequencydomain methods and video watermarking techniques are classified into spatial domain, frequency domain and formatspecific domain

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 light field watermarking by 4D wavelet transform

Unlike common 2D images, the light field representation of a scene delivers spatial and angular description which is of paramount importance for 3D reconstruction. Despite the numerous methods proposed for 2D image watermarking, such methods do not address the angular information of the light field. Hence the exploitation of such methods may cause severe destruction of the angular information. In this paper, we propose a novel method for light field watermarking with extensive consideration of the spatial and angular information. Considering the 4D innate of the light field, the proposed method incorporates 4D wavelet for the purpose of watermarking and converts the heavily-correlated channels from RGB domain to YUV. The robustness of the proposed method has been evaluated against common image processing attacks