23 research outputs found
Data Hiding and Its Applications
Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others
A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder
With the advancement in technology, digital images can easily be transmitted
and stored over the Internet. Encryption is used to avoid illegal interception
of digital images. Encrypting large-sized colour images in their original
dimension generally results in low encryption/decryption speed along with
exerting a burden on the limited bandwidth of the transmission channel. To
address the aforementioned issues, a new encryption scheme for colour images
employing convolutional autoencoder, DNA and chaos is presented in this paper.
The proposed scheme has two main modules, the dimensionality conversion module
using the proposed convolutional autoencoder, and the encryption/decryption
module using DNA and chaos. The dimension of the input colour image is first
reduced from N M 3 to P Q gray-scale image using the
encoder. Encryption and decryption are then performed in the reduced dimension
space. The decrypted gray-scale image is upsampled to obtain the original
colour image having dimension N M 3. The training and
validation accuracy of the proposed autoencoder is 97% and 95%, respectively.
Once the autoencoder is trained, it can be used to reduce and subsequently
increase the dimension of any arbitrary input colour image. The efficacy of the
designed autoencoder has been demonstrated by the successful reconstruction of
the compressed image into the original colour image with negligible perceptual
distortion. The second major contribution presented in this paper is an image
encryption scheme using DNA along with multiple chaotic sequences and
substitution boxes. The security of the proposed image encryption algorithm has
been gauged using several evaluation parameters, such as histogram of the
cipher image, entropy, NPCR, UACI, key sensitivity, contrast, etc. encryption
The dynamics of complex systems. Studies and applications in computer science and biology
Our research has focused on the study of complex dynamics and on their use in both information security and bioinformatics. Our first work has been on chaotic discrete dynamical systems, and links have been established between these dynamics on the one hand, and either random or complex behaviors. Applications on information security are on the pseudorandom numbers generation, hash functions, informationhiding, and on security aspects on wireless sensor networks. On the bioinformatics level, we have applied our studies of complex systems to theevolution of genomes and to protein folding
A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder
With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption/decryption speed along with exerting a burden on the limited bandwidth of the transmission channel. To address the aforementioned issues, a new encryption scheme for colour images employing convolutional autoencoder, DNA and chaos is presented in this paper. The proposed scheme has two main modules, the dimensionality conversion module using the proposed convolutional autoencoder, and the encryption/decryption module using DNA and chaos. The dimension of the input colour image is first reduced from N Ă— M Ă— 3 to P Ă— Q gray-scale image using the encoder. Encryption and decryption are then performed in the reduced dimension space. The decrypted gray-scale image is upsampled to obtain the original colour image having dimension N Ă— M Ă— 3. The training and validation accuracy of the proposed autoencoder is 97% and 95%, respectively. Once the autoencoder is trained, it can be used to reduce and subsequently increase the dimension of any arbitrary input colour image. The efficacy of the designed autoencoder has been demonstrated by the successful reconstruction of the compressed image into the original colour image with negligible perceptual distortion. The second major contribution presented in this paper is an image encryption scheme using DNA along with multiple chaotic sequences and substitution boxes. The security of the proposed image encryption algorithm has been gauged using several evaluation parameters, such as histogram of the cipher image, entropy, NPCR, UACI, key sensitivity, contrast, etc. The experimental results of the proposed scheme demonstrate its effectiveness to perform colour image encryption
Quality Factor terhadap Kapasitas Pesan Rahasia pada Steganografi Citra JPEG dan Kualitas Citra Stego
One of the container media that is available and popular is the Joint Photographic Experts Group (JPEG) format image. This article aims to determine the effect of Quality Factor on the secret message capacity of JPEG image steganography and stego image quality. The quality of an image can actually be seen subjectively with the human eye, but this is relative between each individual. Because the assessment of the human eye varies from person to person. In addition, the effect of Quality Factor on secret message capacity is not yet known whether it has an impact. Therefore, in this study the Quality Factor is used to objectively see the secret message capacity of the JPEG image steganography and the quality of the stego image. The parameter used to determine the quality of an image is the Peak Signal to Noise Ratio (PSNR). PSNR will compare the quality of the original image (before steganography) with the stego image. The test results show that the Q Factor effect can affect the secret message capacity of the JPEG image steganography and the stego image quality. The bigger the Q Factor, the more the message capacity is generated. The greater the Q factor, the better the quality of the resulting stego image
Fractal Analysis
Fractal analysis is becoming more and more common in all walks of life. This includes biomedical engineering, steganography and art. Writing one book on all these topics is a very difficult task. For this reason, this book covers only selected topics. Interested readers will find in this book the topics of image compression, groundwater quality, establishing the downscaling and spatio-temporal scale conversion models of NDVI, modelling and optimization of 3T fractional nonlinear generalized magneto-thermoelastic multi-material, algebraic fractals in steganography, strain induced microstructures in metals and much more. The book will definitely be of interest to scientists dealing with fractal analysis, as well as biomedical engineers or IT engineers. I encourage you to view individual chapters
Entropy in Image Analysis II
Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas
Cryptography and Its Applications in Information Security
Nowadays, mankind is living in a cyber world. Modern technologies involve fast communication links between potentially billions of devices through complex networks (satellite, mobile phone, Internet, Internet of Things (IoT), etc.). The main concern posed by these entangled complex networks is their protection against passive and active attacks that could compromise public security (sabotage, espionage, cyber-terrorism) and privacy. This Special Issue “Cryptography and Its Applications in Information Security” addresses the range of problems related to the security of information in networks and multimedia communications and to bring together researchers, practitioners, and industrials interested by such questions. It consists of eight peer-reviewed papers, however easily understandable, that cover a range of subjects and applications related security of information
Recent Advances in Signal Processing
The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity
Security and Privacy for Modern Wireless Communication Systems
The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks