Applied batch cryptography

The material presented in this thesis may be viewed as comprising two key parts, the first part concerns batch cryptography specifically, whilst the second deals with how this form of cryptography may be applied to security related applications such as electronic cash for improving efficiency of the protocols. The objective of batch cryptography is to devise more efficient primitive cryptographic protocols. In general, these primitives make use of some property such as homomorphism to perform a computationally expensive operation on a collective input set. The idea is to amortise an expensive operation, such as modular exponentiation, over the input. Most of the research work in this field has concentrated on its employment as a batch verifier of digital signatures. It is shown that several new attacks may be launched against these published schemes as some weaknesses are exposed. Another common use of batch cryptography is the simultaneous generation of digital signatures. There is significantly less previous work on this area, and the present schemes have some limited use in practical applications. Several new batch signatures schemes are introduced that improve upon the existing techniques and some practical uses are illustrated. Electronic cash is a technology that demands complex protocols in order to furnish several security properties. These typically include anonymity, traceability of a double spender, and off-line payment features. Presently, the most efficient schemes make use of coin divisibility to withdraw one large financial amount that may be progressively spent with one or more merchants. Several new cash schemes are introduced here that make use of batch cryptography for improving the withdrawal, payment, and deposit of electronic coins. The devised schemes apply both to the batch signature and verification techniques introduced, demonstrating improved performance over the contemporary divisible based structures. The solutions also provide an alternative paradigm for the construction of electronic cash systems. Whilst electronic cash is used as the vehicle for demonstrating the relevance of batch cryptography to security related applications, the applicability of the techniques introduced extends well beyond this.

The design and testing of a daylighting device : optimising the energy and optical performance of Australian commercial buildings

The effective daylighting of multistorey commercial building interiors poses an interesting problem for designers in Australia’s tropical and subtropical context. Given that a building exterior receives adequate sun and skylight as dictated by location-specific factors such as weather, siting and external obstructions; then the availability of daylight throughout its interior is dependant on certain building characteristics: the distance from a window façade (room depth), ceiling or window head height, window size and the visible transmittance of daylighting apertures. The daylighting of general stock, multistorey commercial buildings is made difficult by their design limitations with respect to some of these characteristics. The admission of daylight to these interiors is usually exclusively by vertical windows. Using conventional glazing, such windows can only admit sun and skylight to a depth of approximately 2 times the window height. This penetration depth is typically much less than the depth of the office interiors, so that core areas of these buildings receive little or no daylight. This issue is particularly relevant where deep, open plan office layouts prevail. The resulting interior daylight pattern is a relatively narrow perimeter zone bathed in (sometimes too intense) light, contrasted with a poorly daylit core zone. The broad luminance range this may present to a building occupant’s visual field can be a source of discomfort glare. Furthermore, the need in most tropical and subtropical regions to restrict solar heat gains to building interiors for much of the year has resulted in the widespread use of heavily tinted or reflective glazing on commercial building façades. This strategy reduces the amount of solar radiation admitted to the interior, thereby decreasing daylight levels proportionately throughout. However this technique does little to improve the way light is distributed throughout the office space. Where clear skies dominate weather conditions, at different times of day or year direct sunlight may pass unobstructed through vertical windows causing disability or discomfort glare for building occupants and as such, its admission to an interior must be appropriately controlled. Any daylighting system to be applied to multistorey commercial buildings must consider these design obstacles, and attempt to improve the distribution of daylight throughout these deep, sidelit office spaces without causing glare conditions. The research described in this thesis delineates first the design optimisation and then the actual prototyping and manufacture process of a daylighting device to be applied to such multistorey buildings in tropical and subtropical environments.

Hierarchical models for 2D presence/absence data having ambiguous zeroes: With a biogeographical case study on dingo behaviour

This dissertation is primarily an applied statistical modelling investigation, motivated by a case study comprising real data and real questions. Theoretical questions on modelling and computation of normalization constants arose from pursuit of these data analytic questions. The essence of the thesis can be described as follows. Consider binary data observed on a two-dimensional lattice. A common problem with such data is the ambiguity of zeroes recorded. These may represent zero response given some threshold (presence) or that the threshold has not been triggered (absence). Suppose that the researcher wishes to estimate the effects of covariates on the binary responses, whilst taking into account underlying spatial variation, which is itself of some interest. This situation arises in many contexts and the dingo, cypress and toad case studies described in the motivation chapter are examples of this. Two main approaches to modelling and inference are investigated in this thesis. The first is frequentist and based on generalized linear models, with spatial variation modelled by using a block structure or by smoothing the residuals spatially. The EM algorithm can be used to obtain point estimates, coupled with bootstrapping or asymptotic MLE estimates for standard errors. The second approach is Bayesian and based on a three- or four-tier hierarchical model, comprising a logistic regression with covariates for the data layer, a binary Markov Random field (MRF) for the underlying spatial process, and suitable priors for parameters in these main models. The three-parameter autologistic model is a particular MRF of interest. Markov chain Monte Carlo (MCMC) methods comprising hybrid Metropolis/Gibbs samplers is suitable for computation in this situation. Model performance can be gauged by MCMC diagnostics. Model choice can be assessed by incorporating another tier in the modelling hierarchy. This requires evaluation of a normalization constant, a notoriously difficult problem. Difficulty with estimating the normalization constant for the MRF can be overcome by using a path integral approach, although this is a highly computationally intensive method. Different methods of estimating ratios of normalization constants (N Cs) are investigated, including importance sampling Monte Carlo (ISMC), dependent Monte Carlo based on MCMC simulations (MCMC), and reverse logistic regression (RLR). I develop an idea present though not fully developed in the literature, and propose the Integrated mean canonical statistic (IMCS) method for estimating log NC ratios for binary MRFs. The IMCS method falls within the framework of the newly identified path sampling methods of Gelman & Meng (1998) and outperforms ISMC, MCMC and RLR. It also does not rely on simplifying assumptions, such as ignoring spatio-temporal dependence in the process. A thorough investigation is made of the application of IMCS to the three-parameter Autologistic model. This work introduces background computations required for the full implementation of the four-tier model in Chapter 7. Two different extensions of the three-tier model to a four-tier version are investigated. The first extension incorporates temporal dependence in the underlying spatio-temporal process. The second extensions allows the successes and failures in the data layer to depend on time. The MCMC computational method is extended to incorporate the extra layer. A major contribution of the thesis is the development of a fully Bayesian approach to inference for these hierarchical models for the first time. Note: The author of this thesis has agreed to make it open access but invites people downloading the thesis to send her an email via the 'Contact Author' function.

Development and evaluation of hydrocarbon sorbent materials with the aid of chemometrics

Hydrocarbon spills on roads are a major safety concern for the driving public and can have severe cost impacts both on pavement maintenance and to the economy through disruption to services. The time taken to clean-up spills and re-open roads in a safe driving condition is an issue of increasing concern given traffic levels on major urban arterials. Thus, the primary aim of the research was to develop a sorbent material that facilitates rapid clean-up of road spills. The methodology involved extensive research into a range of materials (organic, inorganic and synthetic sorbents), comprehensive testing in the laboratory, scale-up and field, and product design (i.e. concept to prototype). The study also applied chemometrics to provide consistent, comparative methods of sorbent evaluation and performance. In addition, sorbent materials at every stage were compared against a commercial benchmark. For the first time, the impact of diesel on asphalt pavement has been quantified and assessed in a systematic way. Contrary to conventional thinking and anecdotal observations, the study determined that the action of diesel on asphalt was quite rapid (i.e. hours rather than weeks or months). This significant finding demonstrates the need to minimise the impact of hydrocarbon spills and the potential application of the sorbent option. To better understand the adsorption phenomenon, surface characterisation techniques were applied to selected sorbent materials (i.e. sand, organo-clay and cotton fibre). Brunauer Emmett Teller (BET) and thermal analysis indicated that the main adsorption mechanism for the sorbents occurred on the external surface of the material in the diffusion region (sand and organo-clay) and/or capillaries (cotton fibre). Using environmental scanning electron microscopy (ESEM), it was observed that adsorption by the interfibre capillaries contributed to the high uptake of hydrocarbons by the cotton fibre. Understanding the adsorption mechanism for these sorbents provided some guidance and scientific basis for the selection of materials. The study determined that non-woven cotton mats were ideal sorbent materials for clean-up of hydrocarbon spills. The prototype sorbent was found to perform significantly better than the commercial benchmark, displaying the following key properties: • superior hydrocarbon pick-up from the road pavement; • high hydrocarbon retention capacity under an applied load; • adequate field skid resistance post treatment; • functional and easy to use in the field (e.g. routine handling, transportation, application and recovery); • relatively inexpensive to produce due to the use of raw cotton fibre and simple production process; • environmentally friendly (e.g. renewable materials, non-toxic to environment and operators, and biodegradable); and • rapid response time (e.g. two minutes total clean-up time compared with thirty minutes for reference sorbents). The major outcomes of the research project include: a) development of a specifically designed sorbent material suitable for cleaning up hydrocarbon spills on roads; b) submission of patent application (serial number AU2005905850) for the prototype product; and c) preparation of Commercialisation Strategy to advance the sorbent product to the next phase (i.e. R&D to product commercialisation).

Spatial mapping and map exploitation : a bio-inspired engineering perspective

Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

Experiments in visual localisation around underwater structures

Localisation of an AUV is challenging and a range of inspection applications require relatively accurate positioning information with respect to submerged structures. We have developed a vision based localisation method that uses a 3D model of the structure to be inspected. The system comprises a monocular vision system, a spotlight and a low-cost IMU. Previous methods that attempt to solve the problem in a similar way try and factor out the effects of lighting. Effects, such as shading on curved surfaces or specular reflections, are heavily dependent on the light direction and are difficult to deal with when using existing techniques. The novelty of our method is that we explicitly model the light source. Results are shown of an implementation on a small AUV in clear water at night.

The role of social skills and school connectedness in preadolescent depressive symptoms

In the current study, we tested whether school connectedness mediates more distal deficits in social skills in influencing depressive symptoms in a sample of 127 sixth- and seventh-grade students. Results demonstrated that school connectedness and social skills accounted for 44% and 26% of variance in depressive symptoms respectively and 49% in a combined model. Although the full mediation model hypothesis was not supported, follow-up analyses revealed that school connectedness partially mediated the link between social skills and preadolescent depressive symptoms. Thus, school connectedness appears to play as strong a role in depressive symptoms in this younger preadolescent age group.

Translation of addictions science into practice

Recent advances in the understanding of the genetic, neurochemical, behavioral and cultural underpinnings of addiction have led to rapid advances in the understanding of addiction as a disease. In fact, advances in basic science and the development of new pharmacological and behavioral therapies associated with them are appearing faster than can be assimilated not only by clinical researchers but practitioners and policy makers as well. Translation of science-based addictions knowledge into improved prevention, assessment and treatment, and communication of these changes to researchers and practitioners are significant challenges to the field. The general aim of this book is to summarize current and potential linkages between advances in addiction science and innovations in clinical practice. Whilst this book is primarily focused on translation, it also encompasses some scientific advances that are relevant to dissemination, and the book is itself a tool for disseminating innovative thinking. The goal is to generate interest in application opportunities from both recent research and theoretical advances.