Efficient one-round key exchange in the standard model

We consider one-round key exchange protocols secure in the standard model. The security analysis uses the powerful security model of Canetti and Krawczyk and a natural extension of it to the ID-based setting. It is shown how KEMs can be used in a generic way to obtain two different protocol designs with progressively stronger security guarantees. A detailed analysis of the performance of the protocols is included; surprisingly, when instantiated with specific KEM constructions, the resulting protocols are competitive with the best previous schemes that have proofs only in the random oracle model.

Efficient one-round key exchange in the efficient one-round key exchange in the standard model

We consider one-round key exchange protocols secure in the standard model. The security analysis uses the powerful security model of Canetti and Krawczyk and a natural extension of it to the ID-based setting. It is shown how KEMs can be used in a generic way to obtain two different protocol designs with progressively stronger security guarantees. A detailed analysis of the performance of the protocols is included; surprisingly, when instantiated with specific KEM constructions, the resulting protocols are competitive with the best previous schemes that have proofs only in the random oracle model.

Efficient one-round key exchange in the standard model

We consider one-round key exchange protocols secure in the standard model. The security analysis uses the powerful security model of Canetti and Krawczyk and a natural extension of it to the ID-based setting. It is shown how KEMs can be used in a generic way to obtain two different protocol designs with progressively stronger security guarantees. A detailed analysis of the performance of the protocols is included; surprisingly, when instantiated with specific KEM constructions, the resulting protocols are competitive with the best previous schemes that have proofs only in the random oracle model.

The moment of exchange : risk, vulnerability, responsibility

Any cycle of production and exchange – be it economic, cultural or aesthetic – involves an element of risk. It involves uncertainty, unpredictability, and a potential for new insight and innovation (the boom) as well as blockages, crises and breakdown (the bust). In performance, the risks are plentiful – economic, political, social, physical and psychological. The risks people are willing to take depend on their position in the exchange (performer, producer, venue manager or spectator), and their aesthetic preferences. This paper considers the often uncertain, confronting or ‘risky’ moment of exchange between performer, spectator and culture in Live Art practices. Encompassing body art, autobiographical art, site-specific art and other sorts of performative intervention in the public sphere, Live Art eschews the artifice of theatre, breaking down barriers between art and life, artist and spectator, to speak back to the public sphere, and challenge assumptions about bodies, identities, memories, relationships and histories. In the process, Live Art frequently privileges an uncertain, confrontational or ‘risky’ mode of exchange between performer, spectator and culture, as a way of challenging power structures. This paper examines the moment of exchange in terms of risk, vulnerability, responsibility and ethics. Why the romance with ‘risky’ behaviours and exchanges? Who is really taking a risk? What risk? With whose permission (or lack thereof)? What potential does a ‘risky’ exchange hold to destabilise aesthetic, social or political norms? Where lies the fine line between subversive intervention in the public sphere and sheer self-indulgence? What are the social and ethical implications of a moment of exchange that puts bodies, beliefs or social boundaries at ‘risk’? In this paper, these questions are addressed with reference to historical and contemporary practices under the broadly defined banner of Live Art, from the early work of Abrovamic and Burden, through to contemporary Australian practitioners like Fiona McGregor.

Modeling and Verification of Privacy Enhancing Protocols

Privacy enhancing protocols (PEPs) are a family of protocols that allow secure exchange and management of sensitive user information. They are important in preserving users’ privacy in today’s open environment. Proof of the correctness of PEPs is necessary before they can be deployed. However, the traditional provable security approach, though well established for verifying cryptographic primitives, is not applicable to PEPs. We apply the formal method of Coloured Petri Nets (CPNs) to construct an executable specification of a representative PEP, namely the Private Information Escrow Bound to Multiple Conditions Protocol (PIEMCP). Formal semantics of the CPN specification allow us to reason about various security properties of PIEMCP using state space analysis techniques. This investigation provides us with preliminary insights for modeling and verification of PEPs in general, demonstrating the benefit of applying the CPN-based formal approach to proving the correctness of PEPs.

Measurement properties of the Australian Women's Activity Survey

Purpose: The Australian Women’s Activity Survey (AWAS) was developed based on a systematic review and qualitative research on how to measure activity patterns of women with young children (WYC). AWAS assesses activity performed across five domains (planned activities, employment, childcare, domestic responsibilities and transport), and intensity levels (sitting, light-intensity, brisk walking, moderate-intensity and vigorous-intensity) in a typical week in the past month. The purpose of this study was to assess the test-retest reliability and criterion validity of the AWAS. Methods: WYC completed the AWAS on two occasions 7-d apart (test-retest reliability protocol) and/or wore an MTI ActiGraph accelerometer for 7-d in between (validity protocol). Forty WYC (mean age 35 ± 5yrs) completed the test-retest reliability protocol and 75 WYC (mean age 33 ± 5yrs) completed the validity protocol. Interclass Correlation Coefficients (ICC) between AWAS administrations and Spearman’s Correlation Coefficients (rs) between AWAS and MTI data were calculated. Results: AWAS showed good test-retest reliability (ICC=0.80 (0.65-0.89)) and acceptable criterion validity (rs= 0.28, p=0.01) for measuring weekly health-enhancing physical activity. AWAS also provided repeatable and valid estimates of sitting time (test-retest reliability ICC=0.42 (0.13-0.64), and criterion validity (rs= 0.32, p=0.006)). Conclusion: The measurement properties of the AWAS are comparable to those reported for existing self-report measures of physical activity. However, AWAS offers a more comprehensive and flexible alternative for accurately assessing different domains and intensities of activity relevant to WYC. Future research should investigate whether the AWAS is a suitable measure of intervention efficacy by examining its sensitivity to change.

Multi-factor password-authenticated key exchange

We consider a new form of authenticated key exchange which we call multi-factor password-authenticated key exchange, where session establishment depends on successful authentication of multiple short secrets that are complementary in nature, such as a long-term password and a one-time response, allowing the client and server to be mutually assured of each other's identity without directly disclosing private information to the other party. Multi-factor authentication can provide an enhanced level of assurance in higher-security scenarios such as online banking, virtual private network access, and physical access because a multi-factor protocol is designed to remain secure even if all but one of the factors has been compromised. We introduce a security model for multi-factor password-authenticated key exchange protocols, propose an efficient and secure protocol called MFPAK, and provide a security argument to show that our protocol is secure in this model. Our security model is an extension of the Bellare-Pointcheval-Rogaway security model for password-authenticated key exchange and accommodates an arbitrary number of symmetric and asymmetric authentication factors.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

Experimental study of the mechanical properties of light gauge cold-formed steels at elevated temperatures

In recent times, light gauge cold-formed steel sections have been used extensively as primary load bearing structural members in many applications in the building industry. Fire safety design of structures using such sections has therefore become more important. Deterioration of mechanical properties of yield stress and elasticity modulus is considered the most important factor affecting the performance of steel structures in fires. Hence there is a need to fully understand the mechanical properties of light gauge cold-formed steels at elevated temperatures. A research project based on experimental studies was therefore undertaken to investigate the deterioration of mechanical properties of light gauge cold-formed steels. Tensile coupon tests were undertaken to determine the mechanical properties of these steels made of both low and high strength steels and thicknesses of 0.60, 0.80 and 0.95 mm at temperatures ranging from 20 to 800ºC. Test results showed that the currently available reduction factors are unsafe to use in the fire safety design of cold-formed steel structures. Therefore new predictive equations were developed for the mechanical properties of yield strength and elasticity modulus at elevated temperatures. This paper presents the details of the experimental study, and the results including the developed equations. It also includes details of a stress-strain model for light gauge cold-formed steels at elevated temperatures.

Layered titanate nanofibers as efficient adsorbents for removal of toxic radioactive and heavy metal ions from water

Titanate nanofibers with two formulas, Na2Ti3O7 and Na1.5H0.5Ti3O7, respectively, exhibit ideal properties for removal of radioactive and heavy metal ions in wastewater, such as Sr2+ , Ba2+ (as substitute of 226Ra2+), and Pb2+ ions. These nanofibers can be fabricated readily by a reaction between titania and caustic soda and have structures in which TiO6 octahedra join each other to form layers with negative charges; the sodium cations exist within the interlayer regions and are exchangeable. They can selectively adsorb the bivalent radioactive ions and heavy metal ions from water through ion exchange process. More importantly, such sorption finally induces considerable deformation of the layer structure, resulting in permanent entrapment of the toxic bivalent cations in the fibers so that the toxic ions can be safely deposited. This study highlights that nanoparticles of inorganic ion exchangers with layered structure are potential materials for efficient removal of the toxic ions from contaminated water.

Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.