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.

The Guardian reportage of the UK MP expenses scandal: a case study of computational journalism

The Guardian reportage of the United Kingdom Member of Parliament (MP) expenses scandal of 2009 used crowdsourcing and computational journalism techniques. Computational journalism can be broadly defined as the application of computer science techniques to the activities of journalism. Its foundation lies in computer assisted reporting techniques and its importance is increasing due to the: (a) increasing availability of large scale government datasets for scrutiny; (b) declining cost, increasing power and ease of use of data mining and filtering software; and Web 2.0; and (c) explosion of online public engagement and opinion.. This paper provides a case study of the Guardian MP expenses scandal reportage and reveals some key challenges and opportunities for digital journalism. It finds journalists may increasingly take an active role in understanding, interpreting, verifying and reporting clues or conclusions that arise from the interrogations of datasets (computational journalism). Secondly a distinction should be made between information reportage and computational journalism in the digital realm, just as a distinction might be made between citizen reporting and citizen journalism. Thirdly, an opportunity exists for online news providers to take a ‘curatorial’ role, selecting and making easily available the best data sources for readers to use (information reportage). These activities have always been fundamental to journalism, however the way in which they are undertaken may change. Findings from this paper may suggest opportunities and challenges for the implementation of computational journalism techniques in practice by digital Australian media providers, and further areas of research.

Betting on the underdog : bricolage as an engine of resource advantage

Resource-based theory posits that firms achieve high performance by controlling resources that are rare, valuable and costly for others to duplicate or work around. Yet scholars have been less successful understanding processes and behaviours by which firms develop such resources. We draw on the behavioral theory of bricolage from the entrepreneurship literature to suggest one such mechanism by which firms may develop such resource-based advantages. The core of our argument is that idiosyncratic bundling processes synonymous with bricolage behavior may create advantageous resource positions by (i) allowing resource constrained firms to allocate more of their limited resources to activities that they view as more strategically important, and (ii) increasing the difficulties other firms face in trying to imitate these advantages. Based on this reasoning we develop several hypotheses which we test in the context of several samples from a large, longitudinal, Australian study of new firm development. The results support our arguments that bricolage will improve a firms’ overall resource positions while generating more areas of strong resource advantage and fewer areas of strong resource disadvantage. We find little support, however, for our arguments that bricolage will make a firms’ key resource advantages more difficult for other firms to imitate. We find some support for our argument that the role of bricolage in creating resource advantages will be enhanced by the quality of the opportunity with which a firm is engaged.

The promise of computational journalism.

There are at least four key challenges in the online news environment that computational journalism may address. Firstly, news providers operate in a rapidly evolving environment and larger businesses are typically slower to adapt to market innovations. News consumption patterns have changed and news providers need to find new ways to capture and retain digital users. Meanwhile, declining financial performance has led to cost cuts in mass market newspapers. Finally investigative reporting is typically slow, high cost and may be tedious, and yet is valuable to the reputation of a news provider. Computational journalism involves the application of software and technologies to the activities of journalism, and it draws from the fields of computer science, social science and communications. New technologies may enhance the traditional aims of journalism, or may require “a new breed of people who are midway between technologists and journalists” (Irfan Essa in Mecklin 2009: 3). Historically referred to as ‘computer assisted reporting’, the use of software in online reportage is increasingly valuable due to three factors: larger datasets are becoming publicly available; software is becoming sophisticated and ubiquitous; and the developing Australian digital economy. This paper introduces key elements of computational journalism – it describes why it is needed; what it involves; benefits and challenges; and provides a case study and examples. Computational techniques can quickly provide a solid factual basis for original investigative journalism and may increase interaction with readers, when correctly used. It is a major opportunity to enhance the delivery of original investigative journalism, which ultimately may attract and retain readers online.

Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models

The health of tollbooth workers is seriously threatened by long-term exposure to polluted air from vehicle exhausts. Using traffic data collected at a toll plaza, vehicle movements were simulated by a system dynamics model with different traffic volumes and toll collection procedures. This allowed the average travel time of vehicles to be calculated. A three-dimension Computational Fluid Dynamics (CFD) model was used with a k–ε turbulence model to simulate pollutant dispersion at the toll plaza for different traffic volumes and toll collection procedures. It was shown that pollutant concentration around tollbooths increases as traffic volume increases. Whether traffic volume is low or high (1500 vehicles/h or 2500 vehicles/h), pollutant concentration decreases if electronic toll collection (ETC) is adopted. In addition, pollutant concentration around tollbooths decreases as the proportion of ETC-equipped vehicles increases. However, if the proportion of ETC-equipped vehicles is very low and the traffic volume is not heavy, then pollutant concentration increases as the number of ETC lanes increases.

Stronger difficulty notions for client puzzles and denial-of-service-resistant protocols

Client puzzles are meant to act as a defense against denial of service (DoS) attacks by requiring a client to solve some moderately hard problem before being granted access to a resource. However, recent client puzzle difficulty definitions (Stebila and Ustaoglu, 2009; Chen et al., 2009) do not ensure that solving n puzzles is n times harder than solving one puzzle. Motivated by examples of puzzles where this is the case, we present stronger definitions of difficulty for client puzzles that are meaningful in the context of adversaries with more computational power than required to solve a single puzzle. A protocol using strong client puzzles may still not be secure against DoS attacks if the puzzles are not used in a secure manner. We describe a security model for analyzing the DoS resistance of any protocol in the context of client puzzles and give a generic technique for combining any protocol with a strong client puzzle to obtain a DoS-resistant protocol.

An advanced implicit meshless approach for fractional partial differential equation in computational mechanics

Recently, the numerical modelling and simulation for fractional partial differential equations (FPDE), which have been found with widely applications in modern engineering and sciences, are attracting increased attentions. The current dominant numerical method for modelling of FPDE is the explicit Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings. This paper aims to develop an implicit meshless approach based on the radial basis functions (RBF) for numerical simulation of time fractional diffusion equations. The discrete system of equations is obtained by using the RBF meshless shape functions and the strong-forms. The stability and convergence of this meshless approach are then discussed and theoretically proven. Several numerical examples with different problem domains are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. The results obtained by the meshless formations are also compared with those obtained by FDM in terms of their accuracy and efficiency. It is concluded that the present meshless formulation is very effective for the modelling and simulation for FPDE.

Human resource flexibility and strong ties in entrepreneurial teams

Human resource flexibility is important in entrepreneurial ventures that need to respond to the changing challenges of growing the new business. This research investigates the impact of previously well-known people (strong ties) as entrepreneurial team members on the human resource flexibility of new ventures. Data collected from German founding entrepreneurs in technology-oriented, incubator-based firms shows that choosing a well known individual to join the entrepreneurial team increases the founder's ability to modify the team member's work role, but complicates asking the team member to leave the team if required. Hence, strong ties both increase and reduce human resource flexibility. However, the effect of strong ties on role modifiability is statistically significant only with novice entrepreneurs. These research findings counsel founders to discuss role modification and exit during partnership and entrepreneurial team membership negotiations.

Integrating the resource-based view and transaction cost economics in immigrant business performance

This paper presents a new integrated framework that integrates the resource-based view and transaction cost economics to explain the phenomenon of immigrant entrepreneurship. We extend the existing literature on immigrant entrepreneurship by identifying different types of ethnic network resources and demonstrating how these resources interact with transaction costs in the context of Chinese immigrants. Thus, our study contributes to the literature by providing a theoretical framework which identifies mechanisms immigrant entrepreneurs use to strategically deploy resources to minimize costs and maximize performance outcomes.

Detecting collusive fraud in enterprise resource planning systems

In today's technological age, fraud has become more complicated, and increasingly more difficult to detect, especially when it is collusive in nature. Different fraud surveys showed that the median loss from collusive fraud is much greater than fraud perpetrated by a single person. Despite its prevalence and potentially devastating effects, collusion is commonly overlooked as an organizational risk. Internal auditors often fail to proactively consider collusion in their fraud assessment and detection efforts. In this paper, we consider fraud scenarios with collusion. We present six potentially collusive fraudulent behaviors and show their detection process in an ERP system. We have enhanced our fraud detection framework to utilize aggregation of different sources of logs in order to detect communication and have further enhanced it to render it system-agnostic thus achieving portability and making it generally applicable to all ERP systems.

Patient-specific computational biomechanics for simulating adolescent scoliosis surgery : predicted vs clinical correction for a preliminary series of six patients

Scoliosis is a spinal deformity that requires surgical correction in progressive cases. In order to optimize surgical outcomes, patient-specific finite element models are being developed by our group. In this paper, a single rod anterior correction procedure is simulated for a group of six scoliosis patients. For each patient, personalised model geometry was derived from low-dose CT scans, and clinically measured intra-operative corrective forces were applied. However, tissue material properties were not patient-specific, being derived from existing literature. Clinically, the patient group had a mean initial Cobb angle of 47.3 degrees, which was corrected to 17.5 degrees after surgery. The mean simulated post-operative Cobb angle for the group was 18.1 degrees. Although this represents good agreement between clinical and simulated corrections, the discrepancy between clinical and simulated Cobb angle for individual patients varied between -10.3 and +8.6 degrees, with only three of the six patients matching the clinical result to within accepted Cobb measurement error of +-5 degrees. The results of this study suggest that spinal tissue material properties play an important role in governing the correction obtained during surgery, and that patient-specific modelling approaches must address the question of how to prescribe patient-specific soft tissue properties for spine surgery simulation.

Resource constraints in innovation : the role of bricolage in new venture creation and firm development

The emerging theory of ‘bricolage’ as a resource behaviour represents an attempt to address the central entrepreneurship research problem of making systematic sense of entrepreneurs that sometimes manage to create significant new economic activity under what appears to be severe resource constraints (Baker & Nelson 2005). However, despite growing interest in bricolage there is little large scale empirical evidence about the effectiveness and outcomes of using bricolage processes while developing innovative outcomes in nascent and young firms. In this research we test bricolage using different forms of innovation using data from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project. Our results indicate overall positive results of bricolage with all forms of innovativeness. A discussion of the results and recommended future research is provided.

Computational fluid dynamics analysis of a flat plate photocatalytic reactor for storm and wastewater reuse

A computational fluid dynamics (CFD) analysis has been performed for a flat plate photocatalytic reactor using CFD code FLUENT. Under the simulated conditions (Reynolds number, Re around 2650), a detailed time accurate computation shows the different stages of flow evolution and the effects of finite length of the reactor in creating flow instability, which is important to improve the performance of the reactor for storm and wastewater reuse. The efficiency of a photocatalytic reactor for pollutant decontamination depends on reactor hydrodynamics and configurations. This study aims to investigate the role of different parameters on the optimization of the reactor design for its improved performance. In this regard, more modelling and experimental efforts are ongoing to better understand the interplay of the parameters that influence the performance of the flat plate photocatalytic reactor.

Human resource behaviour simulation in business processes

The structure and dynamics of a modern business environment are very hard to model using traditional methods. Such complexity raises challenges to effective business analysis and improvement. The importance of applying business process simulation to analyze and improve business activities has been widely recognized. However, one remaining challenge is the development of approaches to human resource behavior simulation. To address this problem, we describe a novel simulation approach where intelligent agents are used to simulate human resources by performing allocated work from a workflow management system. The behavior of the intelligent agents is driven a by state transition mechanism called a Hierarchical Task Network (HTN). We demonstrate and validate our simulator via a medical treatment process case study. Analysis of the simulation results shows that the behavior driven by the HTN is consistent with design of the workflow model. We believe these preliminary results support the development of more sophisticated agent-based human resource simulation systems.