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.

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.

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.

IS-impact utility and intuitiveness : a rigorous approach to relevance

The study proposes to test the ‘IS-Impact’ index as Analytic Theory (AT). To (a) methodically evaluate the ‘relevance’ qualities of IS-Impact; namely, Utility & Intuitiveness. In so doing, to (b) document an exemplar of ‘a rigorous approach to relevance’, while (c) treating the overarching study as a higher-order case study having AT as the unit-of-analysis, and assessing adequacy of the 6 AT qualities, both for IS-Impact and for similar taxonomies. Also to (d) look beyond IS-Impact to other forms of Design Science, considering the generality of the AT qualities; and (e) further validating IS-Impact in new system organisation contexts taking account of contemporary understandings of construct theorisation, operationalization and validation.

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.

Utility of routine data sources for feedback on the quality of cancer care: an assessment based on clinical practice guidelines

Background Not all cancer patients receive state-of-the-art care and providing regular feedback to clinicians might reduce this problem. The purpose of this study was to assess the utility of various data sources in providing feedback on the quality of cancer care. Methods Published clinical practice guidelines were used to obtain a list of processes-of-care of interest to clinicians. These were assigned to one of four data categories according to their availability and the marginal cost of using them for feedback. Results Only 8 (3%) of 243 processes-of-care could be measured using population-based registry or administrative inpatient data (lowest cost). A further 119 (49%) could be measured using a core clinical registry, which contains information on important prognostic factors (e.g., clinical stage, physiological reserve, hormone-receptor status). Another 88 (36%) required an expanded clinical registry or medical record review; mainly because they concerned long-term management of disease progression (recurrences and metastases) and 28 (11.5%) required patient interview or audio-taping of consultations because they involved information sharing between clinician and patient. Conclusion The advantages of population-based cancer registries and administrative inpatient data are wide coverage and low cost. The disadvantage is that they currently contain information on only a few processes-of-care. In most jurisdictions, clinical cancer registries, which can be used to report on many more processes-of-care, do not cover smaller hospitals. If we are to provide feedback about all patients, not just those in larger academic hospitals with the most developed data systems, then we need to develop sustainable population-based data systems that capture information on prognostic factors at the time of initial diagnosis and information on management of disease progression.

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.

An approach to access control under uncertainty

In dynamic and uncertain environments such as healthcare, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. The uncertainty stems from the unpredictability of users’ operational needs as well as their private incentives to misuse permissions. In Role Based Access Control (RBAC), a user’s legitimate access request may be denied because its need has not been anticipated by the security administrator. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. This paper introduces a novel approach to access control under uncertainty and presents it in the context of RBAC. By taking insights from the field of economics, in particular the insurance literature, we propose a formal model where the value of resources are explicitly defined and an RBAC policy (entailing those predictable access needs) is only used as a reference point to determine the price each user has to pay for access, as opposed to representing hard and fast rules that are always rigidly applied.