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

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

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

Privacy-Protecting Techniques for Behavioral Data: A Survey

Our behavior (the way we talk, walk, or think) is unique and can be used as a biometric trait. It also correlates with sensitive attributes like emotions. Hence, techniques to protect individuals privacy against unwanted inferences are required. To consolidate knowledge in this area, we systematically reviewed applicable anonymization techniques. We taxonomize and compare existing solutions regarding privacy goals, conceptual operation, advantages, and limitations. Our analysis shows that some behavioral traits (e.g., voice) have received much attention, while others (e.g., eye-gaze, brainwaves) are mostly neglected. We also find that the evaluation methodology of behavioral anonymization techniques can be further improved

Wavelet Theory

The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior

Palmprint Identification Based on Generalization of IrisCode

The development of accurate and reliable security systems is a matter of wide interest, and in this context biometrics is seen as a highly effective automatic mechanism for personal identification. Among biometric technologies, IrisCode developed by Daugman in 1993 is regarded as a highly accurate approach, being able to support real-time personal identification of large databases. Since 1993, on the top of IrisCode, different coding methods have been proposed for iris and fingerprint identification. In this research, I extend and generalize IrisCode for real-time secure palmprint identification. PalmCode, the first coding method for palmprint identification developed by me in 2002, directly applied IrisCode to extract phase information of palmprints as features. However, I observe that the PalmCodes from the different palms are similar, having many 45o streaks. Such structural similarities in the PalmCodes of different palms would reduce the individuality of PalmCodes and the performance of palmprint identification systems. To reduce the correlation between PalmCodes, in this thesis, I employ multiple elliptical Gabor filters with different orientations to compute different PalmCodes and merge them to produce a single feature, called Fusion Code. Experimental results demonstrate that Fusion Code performs better than PalmCode. Based on the results of Fusion Code, I further identify that the orientation fields of palmprints are powerful features. Consequently, Competitive Code, which uses real parts of six Gabor filters to estimate the orientation fields, is developed. To embed the properties of IrisCode, such as high speed matching, in Competitive Code, a novel coding scheme and a bitwise angular distance are proposed. Experimental results demonstrate that Competitive Code is much more effective than other palmprint algorithms. Although many coding methods have been developed based on IrisCode for iris and palmprint identification, we lack a detailed analysis of IrisCode. One of the aims of this research is to provide such analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. This analysis demonstrates that IrisCode is a clustering process with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to a phase parameter and the bitwise hamming distance can be regarded as a bitwise angular distance. In this analysis, I also point out that the theoretical evidence of the imposter binomial distribution of IrisCode is incomplete. I use this analysis to develop a precise phase representation which can enhance iris recognition accuracy and to relate IrisCode and other coding methods. By making use of this analysis, principal component analysis and simulated annealing, near optimal filters for palmprint identification are sought. The near optimal filters perform better than Competitive Code in term of d’ index. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for many years. However, genetically identical palmprints have not been studied. I systemically examine Competitive Code on genetically identical palmprints for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins. As biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analyzed before they are massively deployed in security systems. I propose projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system based on Competitive Code. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks. In addition to brute-force attacks, I address the other three security issues: template re-issuances, also called cancellable biometrics, replay attacks, and database attacks. A random orientation filter bank (ROFB) is used to generate cancellable Competitive Codes for templates re-issuances. Secret messages are hidden in templates to prevent replay and database attacks. This technique can be regarded as template watermarking. A series of analyses is provided to evaluate the security levels of the measures

Palmprint Identification Based on Generalization of IrisCode

The development of accurate and reliable security systems is a matter of wide interest, and in this context biometrics is seen as a highly effective automatic mechanism for personal identification. Among biometric technologies, IrisCode developed by Daugman in 1993 is regarded as a highly accurate approach, being able to support real-time personal identification of large databases. Since 1993, on the top of IrisCode, different coding methods have been proposed for iris and fingerprint identification. In this research, I extend and generalize IrisCode for real-time secure palmprint identification. PalmCode, the first coding method for palmprint identification developed by me in 2002, directly applied IrisCode to extract phase information of palmprints as features. However, I observe that the PalmCodes from the different palms are similar, having many 45o streaks. Such structural similarities in the PalmCodes of different palms would reduce the individuality of PalmCodes and the performance of palmprint identification systems. To reduce the correlation between PalmCodes, in this thesis, I employ multiple elliptical Gabor filters with different orientations to compute different PalmCodes and merge them to produce a single feature, called Fusion Code. Experimental results demonstrate that Fusion Code performs better than PalmCode. Based on the results of Fusion Code, I further identify that the orientation fields of palmprints are powerful features. Consequently, Competitive Code, which uses real parts of six Gabor filters to estimate the orientation fields, is developed. To embed the properties of IrisCode, such as high speed matching, in Competitive Code, a novel coding scheme and a bitwise angular distance are proposed. Experimental results demonstrate that Competitive Code is much more effective than other palmprint algorithms. Although many coding methods have been developed based on IrisCode for iris and palmprint identification, we lack a detailed analysis of IrisCode. One of the aims of this research is to provide such analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. This analysis demonstrates that IrisCode is a clustering process with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to a phase parameter and the bitwise hamming distance can be regarded as a bitwise angular distance. In this analysis, I also point out that the theoretical evidence of the imposter binomial distribution of IrisCode is incomplete. I use this analysis to develop a precise phase representation which can enhance iris recognition accuracy and to relate IrisCode and other coding methods. By making use of this analysis, principal component analysis and simulated annealing, near optimal filters for palmprint identification are sought. The near optimal filters perform better than Competitive Code in term of d’ index. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for many years. However, genetically identical palmprints have not been studied. I systemically examine Competitive Code on genetically identical palmprints for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins. As biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analyzed before they are massively deployed in security systems. I propose projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system based on Competitive Code. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks. In addition to brute-force attacks, I address the other three security issues: template re-issuances, also called cancellable biometrics, replay attacks, and database attacks. A random orientation filter bank (ROFB) is used to generate cancellable Competitive Codes for templates re-issuances. Secret messages are hidden in templates to prevent replay and database attacks. This technique can be regarded as template watermarking. A series of analyses is provided to evaluate the security levels of the measures

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique

OBSERVER-BASED-CONTROLLER FOR INVERTED PENDULUM MODEL

This paper presents a state space control technique for inverted pendulum system. The system is a common classical control problem that has been widely used to test multiple control algorithms because of its nonlinear and unstable behavior. Full state feedback based on pole placement and optimal control is applied to the inverted pendulum system to achieve desired design specification which are 4 seconds settling time and 5% overshoot. The simulation and optimization of the full state feedback controller based on pole placement and optimal control techniques as well as the performance comparison between these techniques is described comprehensively. The comparison is made to choose the most suitable technique for the system that have the best trade-off between settling time and overshoot. Besides that, the observer design is analyzed to see the effect of pole location and noise present in the system

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique