220 research outputs found

    A Spatial Domain Image Steganography Technique Based on Plane Bit Substitution Method

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    Steganography is the art and science of hiding information by embedding data into cover media. In this paper we propose a new method of information hiding in digital image in spatial domain. In this method we use Plane Bit Substitution Method (PBSM) technique in which message bits are embedded into the pixel value(s) of an image. We first, proposed a Steganography transformation machine (STM) for solving Binary operation for manipulation of original image with help to least significant bit (LSB) operator based matching. Second, we use pixel encryption and decryption techniques under theoretical and experimental evolution. Our experimental, techniques are sufficient to discriminate analysis of stego and cover image as each pixel based PBSM, and operand with LSB

    A Study in Image Watermarking Schemes using Neural Networks

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    The digital watermarking technique, an effective way to protect image, has become the research focus on neural network. The purpose of this paper is to provide a brief study on broad theories and discuss the different types of neural networks for image watermarking. Most of the research interest image watermarking based on neural network in discrete wavelet transform or discrete cosine transform. Generally image watermarking based on neural network to solve the problem on to reduce the error, improve the rate of the learning, achieves goods imperceptibility and robustness. It will be useful for researches to implement effective image watermarking by using neural network

    Adaptive digital watermarking scheme based on support vector machines and optimized genetic algorithm

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    Digital watermarking is an effective solution to the problem of copyright protection, thus maintaining the security of digital products in the network. An improved scheme to increase the robustness of embedded information on the basis of discrete cosine transform (DCT) domain is proposed in this study. The embedding process consisted of two main procedures. Firstly, the embedding intensity with support vector machines (SVMs) was adaptively strengthened by training 1600 image blocks which are of different texture and luminance. Secondly, the embedding position with the optimized genetic algorithm (GA) was selected. To optimize GA, the best individual in the first place of each generation directly went into the next generation, and the best individual in the second position participated in the crossover and the mutation process. The transparency reaches 40.5 when GA’s generation number is 200. A case study was conducted on a 256 × 256 standard Lena image with the proposed method. After various attacks (such as cropping, JPEG compression, Gaussian low-pass filtering (3, 0. 5), histogram equalization, and contrast increasing (0.5, 0.6)) on the watermarked image, the extracted watermark was compared with the original one. Results demonstrate that the watermark can be effectively recovered after these attacks. Even though the algorithm is weak against rotation attacks, it provides high quality in imperceptibility and robustness and hence it is a successful candidate for implementing novel image watermarking scheme meeting real timelines

    Digital watermarking in medical images

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/12/2005.This thesis addresses authenticity and integrity of medical images using watermarking. Hospital Information Systems (HIS), Radiology Information Systems (RIS) and Picture Archiving and Communication Systems (P ACS) now form the information infrastructure for today's healthcare as these provide new ways to store, access and distribute medical data that also involve some security risk. Watermarking can be seen as an additional tool for security measures. As the medical tradition is very strict with the quality of biomedical images, the watermarking method must be reversible or if not, region of Interest (ROI) needs to be defined and left intact. Watermarking should also serve as an integrity control and should be able to authenticate the medical image. Three watermarking techniques were proposed. First, Strict Authentication Watermarking (SAW) embeds the digital signature of the image in the ROI and the image can be reverted back to its original value bit by bit if required. Second, Strict Authentication Watermarking with JPEG Compression (SAW-JPEG) uses the same principal as SAW, but is able to survive some degree of JPEG compression. Third, Authentication Watermarking with Tamper Detection and Recovery (AW-TDR) is able to localise tampering, whilst simultaneously reconstructing the original image

    Enhancement of digital grayscale image watermarking using sparse matrix

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    Watermarking is a form of steganography that proved its worth in successfully protecting copyright information. It is the process of embedding data inside an audio or video or image message such that the embedded data is possible to be detected or extracted later. The core focus in watermarking techniques is their performance which is determined by imperceptibility along with robustness and capacity. These properties are often conflicting, which needs to accept some trade-offs between them. Despite the successes recorder in the area of digital watermarking, several challenges continue to persist particularly in the Areas of balancing these factors. This research aims to enhance the the processes in the watermarking technique for archieving imperceptibility with an acceptable balancing and enhance the security. The research proposed a new scheme using sparse matrix for improving the effectiveness of watermarked image using digital wavelet transform and inverse discrete wavelet transform to locate the best place and level in the image to embed the watermark. Sparse matrix is used to enhance the embedding process by selecting the proper coefficient. For more secure watermarking, additional encryption layer is utilized to increase the difficulty towards unauthorized extraction. The proposed technique generated the proper message size for each sub image based on the PSNR, which is used as an indicator for selecting the suitable level of embedding and for detecting the possibility of attacks. The proposed scheme improves watermarking quality by using the sparse matrix to select the appropriate coefficient for embedding. The experiments showed that the proposed scheme enhances 2.8479 dB of quality (PSNR) or equivalent to 5.3 % of improvements. The research proposed scheme achieved better PSNR in comparison with other research

    Digital watermarking methods for data security and authentication

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    Philosophiae Doctor - PhDCryptology is the study of systems that typically originate from a consideration of the ideal circumstances under which secure information exchange is to take place. It involves the study of cryptographic and other processes that might be introduced for breaking the output of such systems - cryptanalysis. This includes the introduction of formal mathematical methods for the design of a cryptosystem and for estimating its theoretical level of securit

    Symmetry-Adapted Machine Learning for Information Security

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    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
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