A test vehicle for compliance with resilience requirements in index-based e-health systems

Increasingly, national and international governments have a strong mandate to develop national e-health systems to enable delivery of much-needed healthcare services. Research is, therefore, needed into appropriate security and reliance structures for the development of health information systems which must be compliant with governmental and alike obligations. The protection of e-health information security is critical to the successful implementation of any e-health initiative. To address this, this paper proposes a security architecture for index-based e-health environments, according to the broad outline of Australia’s National E-health Strategy and National E-health Transition Authority (NEHTA)’s Connectivity Architecture. This proposal, however, could be equally applied to any distributed, index-based health information system involving referencing to disparate health information systems. The practicality of the proposed security architecture is supported through an experimental demonstration. This successful prototype completion demonstrates the comprehensibility of the proposed architecture, and the clarity and feasibility of system specifications, in enabling ready development of such a system. This test vehicle has also indicated a number of parameters that need to be considered in any national indexed-based e-health system design with reasonable levels of system security. This paper has identified the need for evaluation of the levels of education, training, and expertise required to create such a system.

State convergence in the initialisation of stream ciphers

An initialisation process is a key component in modern stream cipher design. A well-designed initialisation process should ensure that each key-IV pair generates a different key stream. In this paper, we analyse two ciphers, A5/1 and Mixer, for which this does not happen due to state convergence. We show how the state convergence problem occurs and estimate the effective key-space in each case.

Enhancing business continuity management capacities in the insurance industry : a Southeast Asian perspective

As a resilience enhancing practice, business continuity management (BCM) can play an important role in aiding preparation of the insurance industry for coping with the losses incurred by major discontinuity incidents: regardless of cause. Acknowledging the increasing frequency of unpredictable man-made disasters and natural catastrophes, the insurance industry would benefit from examining and implementing, where suitable, key elements of BCM. Such strategic decisions would assist insurers and re-insurers collectively to enhance mutual capability to respond to, and recover from, the impact of significant losses. This paper presents a comparison of opinions about BCM practitioners in both retail and re-insurance companies on the importance of generic continuity practices with actual levels of BCM practice across the two industry groups in Southeast Asia. It suggests means by which multi-lateral cooperation across Asian economies and between retail and re-insurance market segments might enhance the viability of the insurance industry in the face of increased stress from major natural and socio-technical hazards.

Extending the task of diarization to speaker attribution

In this paper we extend the concept of speaker annotation within a single-recording, or speaker diarization, to a collection wide approach we call speaker attribution. Accordingly, speaker attribution is the task of clustering expectantly homogenous intersession clusters obtained using diarization according to common cross-recording identities. The result of attribution is a collection of spoken audio across multiple recordings attributed to speaker identities. In this paper, an attribution system is proposed using mean-only MAP adaptation of a combined-gender UBM to model clusters from a perfect diarization system, as well as a JFA-based system with session variability compensation. The normalized cross-likelihood ratio is calculated for each pair of clusters to construct an attribution matrix and the complete linkage algorithm is employed to conduct clustering of the inter-session clusters. A matched cluster purity and coverage of 87.1% was obtained on the NIST 2008 SRE corpus.

Combating computer crime : an international perspective

Given the serious nature of computer crime, and its global nature and implications, it is clear that there is a crucial need for a common understanding of such criminal activity internationally in order to deal with it effectively. Research into the extent to which legislation, international initiatives, and policy and procedures to combat and investigate computer crime are consistent globally is therefore of enormous importance. The challenge is to study, analyse, and compare the policies and practices of combating computer crime under different jurisdictions in order to identify the extent to which they are consistent with each other and with international guidelines; and the extent of their successes and limitations. The purpose ultimately is to identify areas where improvements are needed and what those improvements should be. This thesis examines approaches used for combating computer crime, including money laundering, in Australia, the UAE, the UK and the USA, four countries which represent a spectrum of economic development and culture. It does so in the context of the guidelines of international organizations such as the Council of Europe (CoE) and the Financial Action Task Force (FATF). In the case of the UAE, we examine also the cultural influences which differentiate it from the other three countries and which has necessarily been a factor in shaping its approaches for countering money laundering in particular. The thesis concludes that because of the transnational nature of computer crime there is a need internationally for further harmonisation of approaches for combating computer crime. The specific contributions of the thesis are as follows: „h Developing a new unified comprehensive taxonomy of computer crime based upon the dual characteristics of the role of the computer and the contextual nature of the crime „h Revealing differences in computer crime legislation in Australia, the UAE, the UK and the USA, and how they correspond to the CoE Convention on Cybercrime and identifying a new framework to develop harmonised computer crime or cybercrime legislation globally „h Identifying some important issues that continue to create problems for law enforcement agencies such as insufficient resources, coping internationally with computer crime legislation that differs between countries, having comprehensive documented procedures and guidelines for combating computer crime, and reporting and recording of computer crime offences as distinct from other forms of crime „h Completing the most comprehensive study currently available regarding the extent of money laundered in four such developed or fast developing countries „h Identifying that the UK and the USA are the most advanced with regard to anti-money laundering and combating the financing of terrorism (AML/CFT) systems among the four countries based on compliance with the FATF recommendations. In addition, the thesis has identified that local factors have affected how the UAE has implemented its financial and AML/CFT systems and reveals that such local and cultural factors should be taken into account when implementing or evaluating any country¡¦s AML/CFT system.

Fourier active appearance models

Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.

An efficient public key management system : an application in vehicular ad hoc networks

The major purpose of Vehicular Ad Hoc Networks (VANETs) is to provide safety-related message access for motorists to react or make a life-critical decision for road safety enhancement. Accessing safety-related information through the use of VANET communications, therefore, must be protected, as motorists may make critical decisions in response to emergency situations in VANETs. If introducing security services into VANETs causes considerable transmission latency or processing delays, this would defeat the purpose of using VANETs to improve road safety. Current research in secure messaging for VANETs appears to focus on employing certificate-based Public Key Cryptosystem (PKC) to support security. The security overhead of such a scheme, however, creates a transmission delay and introduces a time-consuming verification process to VANET communications. This paper proposes an efficient public key management system for VANETs: the Public Key Registry (PKR) system. Not only does this paper demonstrate that the proposed PKR system can maintain security, but it also asserts that it can improve overall performance and scalability at a lower cost, compared to the certificate-based PKC scheme. It is believed that the proposed PKR system will create a new dimension to the key management and verification services for VANETs.

Defending web services against denial of service attacks using client puzzles

The interoperable and loosely-coupled web services architecture, while beneficial, can be resource-intensive, and is thus susceptible to denial of service (DoS) attacks in which an attacker can use a relatively insignificant amount of resources to exhaust the computational resources of a web service. We investigate the effectiveness of defending web services from DoS attacks using client puzzles, a cryptographic countermeasure which provides a form of gradual authentication by requiring the client to solve some computationally difficult problems before access is granted. In particular, we describe a mechanism for integrating a hash-based puzzle into existing web services frameworks and analyze the effectiveness of the countermeasure using a variety of scenarios on a network testbed. Client puzzles are an effective defence against flooding attacks. They can also mitigate certain types of semantic-based attacks, although they may not be the optimal solution.

Wide baseline correspondence extraction beyond local features

Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature matches. Methods of improving the accuracy of a set of putative matches, eliminating incorrect matches and extracting large numbers of additional correspondences are explored. It is assumed that knowledge of the camera geometry is not available and not immediately recoverable. The new techniques are evaluated by means of an epipolar geometry estimation task. It is shown that these methods enable the computation of camera geometry in many cases where existing feature extractors cannot produce sufficient numbers of accurate correspondences.

Gap analysis of intrusion detection in smart grids

Given the recent emergence of the smart grid and smart grid related technologies, their security is a prime concern. Intrusion detection provides a second line of defense. However, conventional intrusion detection systems (IDSs) are unable to adequately address the unique requirements of the smart grid. This paper presents a gap analysis of contemporary IDSs from a smart grid perspective. This paper highlights the lack of adequate intrusion detection within the smart grid and discusses the limitations of current IDSs approaches. The gap analysis identifies current IDSs as being unsuited to smart grid application without significant changes to address smart grid specific requirements.

Multi-objective optimisation of bijective s-boxes

In this paper we investigate the heuristic construction of bijective s-boxes that satisfy a wide range of cryptographic criteria including algebraic complexity, high nonlinearity, low autocorrelation and have none of the known weaknesses including linear structures, fixed points or linear redundancy. We demonstrate that the power mappings can be evolved (by iterated mutation operators alone) to generate bijective s-boxes with the best known tradeoffs among the considered criteria. The s-boxes found are suitable for use directly in modern encryption algorithms.