Design and Analysis of Reversible Data Hiding Using Hybrid Cryptographic and Steganographic approaches for Multiple Images

Data concealing is the process of including some helpful information on images. The majority of sensitive applications, such sending authentication data, benefit from data hiding. Reversible data hiding (RDH), also known as invertible or lossless data hiding in the field of signal processing, has been the subject of a lot of study. A piece of data that may be recovered from an image to disclose the original image is inserted into the image during the RDH process to generate a watermarked image. Lossless data hiding is being investigated as a strong and popular way to protect copyright in many sensitive applications, such as law enforcement, medical diagnostics, and remote sensing. Visible and invisible watermarking are the two types of watermarking algorithms. The watermark must be bold and clearly apparent in order to be visible. To be utilized for invisible watermarking, the watermark must be robust and visibly transparent. Reversible data hiding (RDH) creates a marked signal by encoding a piece of data into the host signal. Once the embedded data has been recovered, the original signal may be accurately retrieved. For photos shot in poor illumination, visual quality is more important than a high PSNR number. The DH method increases the contrast of the host picture while maintaining a high PSNR value. Histogram equalization may also be done concurrently by repeating the embedding process in order to relocate the top two bins in the input image's histogram for data embedding. It's critical to assess the images after data concealment to see how much the contrast has increased. Common picture quality assessments include peak signal to noise ratio (PSNR), relative structural similarity (RSS), relative mean brightness error (RMBE), relative entropy error (REE), relative contrast error (RCE), and global contrast factor (GCF). The main objective of this paper is to investigate the various quantitative metrics for evaluating contrast enhancement. The results show that the visual quality may be preserved by including a sufficient number of message bits in the input photographs

Comparative Study and Design Light Weight Data Security System for Secure Data Transmission in Internet of Things

Internet of things is shortened as IoT. Today IoT is a key and abrogating subject of the specialized and social importance. Results of buyers, things and vehicles, industry based and fundamental segments, sensors, and other everyday items are converged with network of internet and the solid information abilities which guarantee to change the sort in which we work and live. The proposed work demonstrates the implementation of symmetric key lightweight algorithm for secured data transmission of images and text using image encryption system as well as reversible data hiding system. In this paper, implemented symmetric key cryptography for various formats of images, as well as real time image acquisition system has been designed in the form of graphical user interface. Reversible data hiding system has also been designed for secure data transmission system

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

PERFORMANCE ANALYSIS OF DIFFERENT SCHEMES FOR TRANSMISSION OF WATERMARKED MEDICAL IMAGES OVER FADING CHANNELS

ABSTRACT Performance Analysis of Different Schemes for Transmission of Watermarked Medical images over Fading Channels Praveen Kumar Korrai In this thesis, we investigate different types of robust schemes for transmission of medical images with concealed patient information as a watermark. In these schemes, spatial domain digital watermarking technique is adapted to embed the patient information as a watermark into the lower order bits of the medical images to reduce the storage and transmission overheads. The watermark, which comprises text data, is encrypted to prevent unauthorized access of data. To enhance the robustness of the embedded information, the encrypted watermark is coded by concatenation of Reed Solomon (RS) and low density parity check (LDPC) codes. A robust scheme for transmission of watermarked images over impulsive noisy wireless channels is first proposed and its performance analyzed. In this scheme, the bursty wireless channel is simulated by adding impulse noise to the watermark embedded image. Furthermore, turbo channel coding is used to correct the transmission errors over impulsive noisy wireless channels. However, single input single output (SISO) channel capacity is not enough to provide modern wireless services such as data and multimedia messaging services. Further, it is not reliable due to multipath fading. To overcome these problems, a multiple-input multiple-output (MIMO) transmission scheme in which multiple antennas are used at both the transmitter and the receiver has emerged as one of the most significant technical breakthroughs in modern wireless communications. MIMO can improve the channel capacity and provide diversity gain. Hence, a scheme with a MIMO channel is proposed for the transmission of watermarked medical images over Rayleigh flat fading channels and its performance analyzed using MIMO maximum likelihood detector at the receiver. We present another scheme, namely, MIMO space frequency block coded OFDM (MIMO SFBC OFDM) in this thesis for transmission of watermarked medical images over Rayleigh fading channels to mitigate the detrimental effects due to frequency selective fading. The performance of this MIMO SFBC OFDM scheme is analyzed and compared with that of SISO-OFDM using minimum mean square error V-BLAST- based detection at the receiver. The efficacy of the different proposed schemes is illustrated through implementation results on watermarked medical images

Spread Spectrum Watermarking: Principles and Applications in Fading Channel

ISBN 978-953-51-0618-

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

Copyright protection of scalar and multimedia sensor network data using digital watermarking

This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN