Strengthening and formally verifying privacy in identity management systems

In a digital world, users’ Personally Identifiable Information (PII) is normally managed with a system called an Identity Management System (IMS). There are many types of IMSs. There are situations when two or more IMSs need to communicate with each other (such as when a service provider needs to obtain some identity information about a user from a trusted identity provider). There could be interoperability issues when communicating parties use different types of IMS. To facilitate interoperability between different IMSs, an Identity Meta System (IMetS) is normally used. An IMetS can, at least theoretically, join various types of IMSs to make them interoperable and give users the illusion that they are interacting with just one IMS. However, due to the complexity of an IMS, attempting to join various types of IMSs is a technically challenging task, let alone assessing how well an IMetS manages to integrate these IMSs. The first contribution of this thesis is the development of a generic IMS model called the Layered Identity Infrastructure Model (LIIM). Using this model, we develop a set of properties that an ideal IMetS should provide. This idealized form is then used as a benchmark to evaluate existing IMetSs. Different types of IMS provide varying levels of privacy protection support. Unfortunately, as observed by Jøsang et al (2007), there is insufficient privacy protection in many of the existing IMSs. In this thesis, we study and extend a type of privacy enhancing technology known as an Anonymous Credential System (ACS). In particular, we extend the ACS which is built on the cryptographic primitives proposed by Camenisch, Lysyanskaya, and Shoup. We call this system the Camenisch, Lysyanskaya, Shoup - Anonymous Credential System (CLS-ACS). The goal of CLS-ACS is to let users be as anonymous as possible. Unfortunately, CLS-ACS has problems, including (1) the concentration of power to a single entity - known as the Anonymity Revocation Manager (ARM) - who, if malicious, can trivially reveal a user’s PII (resulting in an illegal revocation of the user’s anonymity), and (2) poor performance due to the resource-intensive cryptographic operations required. The second and third contributions of this thesis are the proposal of two protocols that reduce the trust dependencies on the ARM during users’ anonymity revocation. Both protocols distribute trust from the ARM to a set of n referees (n > 1), resulting in a significant reduction of the probability of an anonymity revocation being performed illegally. The first protocol, called the User Centric Anonymity Revocation Protocol (UCARP), allows a user’s anonymity to be revoked in a user-centric manner (that is, the user is aware that his/her anonymity is about to be revoked). The second protocol, called the Anonymity Revocation Protocol with Re-encryption (ARPR), allows a user’s anonymity to be revoked by a service provider in an accountable manner (that is, there is a clear mechanism to determine which entity who can eventually learn - and possibly misuse - the identity of the user). The fourth contribution of this thesis is the proposal of a protocol called the Private Information Escrow bound to Multiple Conditions Protocol (PIEMCP). This protocol is designed to address the performance issue of CLS-ACS by applying the CLS-ACS in a federated single sign-on (FSSO) environment. Our analysis shows that PIEMCP can both reduce the amount of expensive modular exponentiation operations required and lower the risk of illegal revocation of users’ anonymity. Finally, the protocols proposed in this thesis are complex and need to be formally evaluated to ensure that their required security properties are satisfied. In this thesis, we use Coloured Petri nets (CPNs) and its corresponding state space analysis techniques. All of the protocols proposed in this thesis have been formally modeled and verified using these formal techniques. Therefore, the fifth contribution of this thesis is a demonstration of the applicability of CPN and its corresponding analysis techniques in modeling and verifying privacy enhancing protocols. To our knowledge, this is the first time that CPN has been comprehensively applied to model and verify privacy enhancing protocols. From our experience, we also propose several CPN modeling approaches, including complex cryptographic primitives (such as zero-knowledge proof protocol) modeling, attack parameterization, and others. The proposed approaches can be applied to other security protocols, not just privacy enhancing protocols.

Using TAM to examine consumer acceptance of a mobile phone assisted smoking cessation program in Australia

This paper study examines Australian smokers’ perceptions of a potential SMS-assisted smoking cessation program. Using TAM we tested perceived ease of use, perceived usefulness and subjective norms on intentions to use this cessation program if it was available. Findings show that perceived usefulness and subjective norms were the significant predictors of intentions to use. Perceived ease of use did not directly influence this outcome instead it has an indirect influence through perceived usefulness. These preliminary findings can be built upon through introducing additional variables to help practitioners better understand consumer acceptance when marketing e-health programs such as this.

Export decisions within Taiwanese electrical and electronic SMEs : the role of management characteristics and attitudes

In this globalized environment, Taiwanese firms have been very successful in achieving growth via international market expansion. In particular, the Taiwanese electronics industry has shown a dynamism lacking in comparable industries around the world. However, in recent years there has been a move by many of the larger Taiwanese manufacturing firms to outsource their manufacturing to low-cost producers such as China in order to remain competitive. Conversely, most Taiwanese small- to medium-sized enterprises (SMEs) have retained their production facilities in Taiwan. These SMEs seek to expand their sales beyond the domestic market by employing an export strategy, making a significant socioeconomic contribution to the domestic and regional economies. This paper highlights the key dimensions such as enhancing factors (benefits/advantages), inhibiting factors (barriers/costs), and managerial factors (characteristics/commitment) that play an important role in the internationalization of SMEs located within the Taiwanese electronics industry. A logistic regression model is used to predict the probability of a firm being an exporter.

Fast and accurate phonetic spoken term detection

For the first time in human history, large volumes of spoken audio are being broadcast, made available on the internet, archived, and monitored for surveillance every day. New technologies are urgently required to unlock these vast and powerful stores of information. Spoken Term Detection (STD) systems provide access to speech collections by detecting individual occurrences of specified search terms. The aim of this work is to develop improved STD solutions based on phonetic indexing. In particular, this work aims to develop phonetic STD systems for applications that require open-vocabulary search, fast indexing and search speeds, and accurate term detection. Within this scope, novel contributions are made within two research themes, that is, accommodating phone recognition errors and, secondly, modelling uncertainty with probabilistic scores. A state-of-the-art Dynamic Match Lattice Spotting (DMLS) system is used to address the problem of accommodating phone recognition errors with approximate phone sequence matching. Extensive experimentation on the use of DMLS is carried out and a number of novel enhancements are developed that provide for faster indexing, faster search, and improved accuracy. Firstly, a novel comparison of methods for deriving a phone error cost model is presented to improve STD accuracy, resulting in up to a 33% improvement in the Figure of Merit. A method is also presented for drastically increasing the speed of DMLS search by at least an order of magnitude with no loss in search accuracy. An investigation is then presented of the effects of increasing indexing speed for DMLS, by using simpler modelling during phone decoding, with results highlighting the trade-off between indexing speed, search speed and search accuracy. The Figure of Merit is further improved by up to 25% using a novel proposal to utilise word-level language modelling during DMLS indexing. Analysis shows that this use of language modelling can, however, be unhelpful or even disadvantageous for terms with a very low language model probability. The DMLS approach to STD involves generating an index of phone sequences using phone recognition. An alternative approach to phonetic STD is also investigated that instead indexes probabilistic acoustic scores in the form of a posterior-feature matrix. A state-of-the-art system is described and its use for STD is explored through several experiments on spontaneous conversational telephone speech. A novel technique and framework is proposed for discriminatively training such a system to directly maximise the Figure of Merit. This results in a 13% improvement in the Figure of Merit on held-out data. The framework is also found to be particularly useful for index compression in conjunction with the proposed optimisation technique, providing for a substantial index compression factor in addition to an overall gain in the Figure of Merit. These contributions significantly advance the state-of-the-art in phonetic STD, by improving the utility of such systems in a wide range of applications.

aa-cell in practice : an approach to musical live coding

Live coding performances provide a context with particular demands and limitations for music making. In this paper we discuss how as the live coding duo aa-cell we have responded to these challenges, and what this experience has revealed about the computational representation of music and approaches to interactive computer music performance. In particular we have identified several effective and efficient processes that underpin our practice including probability, linearity, periodicity, set theory, and recursion and describe how these are applied and combined to build sophisticated musical structures. In addition, we outline aspects of our performance practice that respond to the improvisational, collaborative and communicative requirements of musical live coding.

Depression among Chinese stroke survivors six months after discharge from a rehabilitation hospital

Aim and objective: The primary aim was to examine the prevalence of poststroke depression in Chinese stroke survivors six months after discharge from a rehabilitation hospital. A second aim was to determine whether six-month poststroke depression was associated with psychological, social and physical outcomes and demographic variables.---------- Background: There has been increasing recognition of the influence of depression on poststroke recovery. While some previous studies report associations between depression and social, psychological, physical and clinical outcomes, few studies had sufficient sample sizes for regression analysis thereby limiting the clinical applicability of their findings. ---------- Design: A cross-sectional design was used.---------- Method: Data were collected from 124 male and 86 female stroke survivors (mean age 71Æ7, SD 10Æ2 years). The Geriatric Depression Scale was used to measure depression, the State Self-esteem Scale to measure state self-esteem, the London Handicap Scale to measure participation restriction, the Social Support Questionnaire to measure satisfaction with social support and the Modified Barthel Index to measure functional ability. Results. Forty-two survivors (20Æ5%) reported mild and 33 (16Æ1%) reported severe depression. The presence of depression was associated with low levels of state self-esteem, social support satisfaction and functional ability. Logistic regression analysis revealed that these variables were statistically significant in predicting the probability of having depression (p < 0Æ05). ---------- Conclusions: Analyses in the present study revealed distinct patterns of correlates of depression, and the results were in agreement with prior studies that depression has a consistent positive ssociation with physical disability, living arrangements and social support and no significant association with the different types of brain lesion. Relevance to clinical practice. There is a need, routinely, to assess stroke survivors for depression and, where necessary, to intervene with the aim of enhancing psychological and social well-being.

A test of podcasting effectiveness for lecture revision

It is important to understand how student performance when higher education is delivered by via new technology. Podcasting is a relatively recent new technology gaining widespread use across the world. We present the results of a quasi-experimental research project that finds when podcasts are used as a revision tool, student performance in Accounting improves. We highlight that aligning podcast use with pedagological design is important and discuss constraints on and barriers to the use of podcasting in higher education.

Comparing cost uplift in infrastructure delivery methods : a case based approach

The alliance project delivery method is used for approximately one third of all Australian government infrastructure projects representing $8-$10 billion per annum. Despite its widespread use, little is known about the differences between estimated project cost and actual cost over the project lifecycle. This paper presents the findings of research into 14 Australian government alliance case studies investigating the observed cost uplift over each project’s lifecycle. I find that significant cost uplift is likely and that this uplift is greater than that afflicting traditional delivery methods. Furthermore, most of the cost uplift occurs at a different place in the project lifecycle, namely between Business Case and Contractual Commitment.

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

Asset health prediction using condition indicators and operating environment indicators : a case study

Prognostics and asset life prediction is one of research potentials in engineering asset health management. We previously developed the Explicit Hazard Model (EHM) to effectively and explicitly predict asset life using three types of information: population characteristics; condition indicators; and operating environment indicators. We have formerly studied the application of both the semi-parametric EHM and non-parametric EHM to the survival probability estimation in the reliability field. The survival time in these models is dependent not only upon the age of the asset monitored, but also upon the condition and operating environment information obtained. This paper is a further study of the semi-parametric and non-parametric EHMs to the hazard and residual life prediction of a set of resistance elements. The resistance elements were used as corrosion sensors for measuring the atmospheric corrosion rate in a laboratory experiment. In this paper, the estimated hazard of the resistance element using the semi-parametric EHM and the non-parametric EHM is compared to the traditional Weibull model and the Aalen Linear Regression Model (ALRM), respectively. Due to assuming a Weibull distribution in the baseline hazard of the semi-parametric EHM, the estimated hazard using this model is compared to the traditional Weibull model. The estimated hazard using the non-parametric EHM is compared to ALRM which is a well-known non-parametric covariate-based hazard model. At last, the predicted residual life of the resistance element using both EHMs is compared to the actual life data.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

Predicting single-vehicle fatal crashes for two-lane rural highways in Southeastern United States

The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes and as such remains a focus of considerable safety research. The Georgia Department of Transportation spearheaded a regional fatal crash analysis to identify various safety performances of two-lane rural highways and to offer guidance for identifying suitable countermeasures with which to mitigate fatal crashes. The fatal crash data used in this study were compiled from Alabama, Georgia, Mississippi, and South Carolina. The database, developed for an earlier study, included 557 randomly selected fatal crashes from 1997 or 1998 or both (this varied by state). Each participating state identified the candidate crashes and performed physical or video site visits to construct crash databases with enhance site-specific information. Motivated by the hypothesis that single- and multiple-vehicle crashes arise from fundamentally different circumstances, the research team applied binary logit models to predict the probability that a fatal crash is a single-vehicle run-off-road fatal crash given roadway design characteristics, roadside environment features, and traffic conditions proximal to the crash site. A wide variety of factors appears to influence or be associated with single-vehicle fatal crashes. In a model transferability assessment, the authors determined that lane width, horizontal curvature, and ambient lighting are the only three significant variables that are consistent for single-vehicle run-off-road crashes for all study locations.