Semantic Security for E-Health: A Case Study in Enhanced Access Control

Data collection, access and usage are essential for many forms of collaborative research. E-Health represents one area with much to gain by sharing of data across organisational boundaries. In such contexts, security and access control are essential to protect the often complex, privacy and information governance concerns of associated stakeholders. In this paper we argue that semantic technologies have unique benefits for specification and enforcement of security policies that cross organisation boundaries. We illustrate this through a case study based around the International Niemann-Pick Disease (NPD) Registry (www.inpdr.org) - which typifies many current e-Health security processes and policies. We show how approaches based upon ontology-based policy specification overcome many of the current security challenges facing the development of such systems and enhance access control by leveraging existing security information associated with clinical collaborators

Semantic privacy-preserving framework for electronic health record linkage

The combination of digitized health information and web-based technologies offers many possibilities for data analysis and business intelligence. In the healthcare and biomedical research domain, applications depending on electronic health records (EHRs) identify privacy preservation as a major concern. Existing solutions cannot always satisfy the evolving research demands such as linking patient records across organizational boundaries due to the potential for patient re-identification. In this work, we show how semantic methods can be applied to support the formulation and enforcement of access control policy whilst ensuring that privacy leakage can be detected and prevented. The work is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN – www.addn.org.au), the national paediatric type-1 diabetes data registry, and the Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) platform that supports Australia-wide access to urban and built environment data sets. We demonstrate that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, finer-grained access control encompassing data risk disclosure mechanisms can be supported. We discuss the contributions that can be made using this approach to socio-economic development and political management within business systems, and especially those situations where secure data access and data linkage is required

Advanced Security Infrastructures for Grid Education

This paper describes the research conducted into advanced authorization infrastructures at the National e-Science Centre (NeSC) at the University of Glasgow and their application to support a teaching environment as part of the Dynamic Virtual Organisations in e-Science Education (DyVOSE) project. We outline the lessons learnt in teaching Grid computing and rolling out the associated security authorisation infrastructures, and describe our plans for a future, extended security infrastructure for dynamic establishment of inter-institutional virtual organisations (VO) in the education domain

Semantic-Based Privacy Protection of Electronic Health Records for Collaborative Research

Combined health information and web-based technologies can be used to support healthcare and research activities associated with electronic health records (EHRs). EHRs used for research purposes demand privacy, confidentiality and all information governance concerns are addressed. However, existing solutions are unable to meet the evolving research needs especially when supporting data access and linkage across organization boundaries. In this work, we show how semantic methods can aid in the specification and enforcement of policies for privacy protection. This is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN), the national paediatric type-1 diabetes data registry and the Australian Urban Research Infrastructure Network (AURIN) platform that supports Australia-wide access to urban and built environment data sets. Specifically we show that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, we are able to support fine-grained privacy-preserving policies leveraging semantic reasoning that is not directly available in XACML or other existing security policy specification languages

Machine Learning-based Classification of Birds through Birdsong

Audio sound recognition and classification is used for many tasks and applications including human voice recognition, music recognition and audio tagging. In this paper we apply Mel Frequency Cepstral Coefficients (MFCC) in combination with a range of machine learning models to identify (Australian) birds from publicly available audio files of their birdsong. We present approaches used for data processing and augmentation and compare the results of various state of the art machine learning models. We achieve an overall accuracy of 91% for the top-5 birds from the 30 selected as the case study. Applying the models to more challenging and diverse audio files comprising 152 bird species, we achieve an accuracy of 58

Experiences modelling and using object-oriented telecommunication service frameworks in SDL

This paper describes experiences in using SDL and its associated tools to create telecommunication services by producing and specialising object-oriented frameworks. The chosen approach recognises the need for the rapid creation of validated telecommunication services. It introduces two stages to service creation. Firstly a software expert produces a service framework, and secondly a telecommunications ‘business consultant' specialises the framework by means of graphical tools to rapidly produce services. Here the focus is given to the underlying technology required. In particular, the advantages and disadvantages of SDL and tools for this purpose are highlighted

Are tiled display walls needed for astronomy?

Clustering commodity displays into a Tiled Display Wall (TDW) provides a cost-effective way to create an extremely high resolution display, capable of approaching the image sizes now gen- erated by modern astronomical instruments. Astronomers face the challenge of inspecting single large images, many similar images simultaneously, and heterogeneous but related content. Many research institutions have constructed TDWs on the basis that they will improve the scientific outcomes of astronomical imagery. We test this concept by presenting sample images to astronomers and non- astronomers using a standard desktop display (SDD) and a TDW. These samples include standard English words, wide field galaxy surveys and nebulae mosaics from the Hubble telescope. These experiments show that TDWs provide a better environment for searching for small targets in large images than SDDs. It also shows that astronomers tend to be better at searching images for targets than non-astronomers, both groups are generally better when employing physical navigation as opposed to virtual navigation, and that the combination of two non-astronomers using a TDW rivals the experience of a single astronomer. However, there is also a large distribution in aptitude amongst the participants and the nature of the content also plays a significant role is success.Comment: 19 pages, 15 figures, accepted for publication in PASA (Publications of the Astronomical Society of Australia

A Semantic-Based K-Anonymity Scheme for Health Record Linkage

Record linkage is a technique for integrating data from sources or providers where direct access to the data is not possible due to security and privacy considerations. This is a very common scenario for medical data, as patient privacy is a significant concern. To avoid privacy leakage, researchers have adopted k-anonymity to protect raw data from re-identification however they cannot avoid associated information loss, e.g. due to generalisation. Given that individual-level data is often not disclosed in the linkage cases, but yet remains potentially re-discoverable, we propose semantic-based linkage k-anonymity to de-identify record linkage with fewer generalisations and eliminate inference disclosure through semantic reasoning

Semantic-Based Policy Composition for Privacy-Demanding Data Linkage

Record linkage can be used to support current and future health research across populations however such approaches give rise to many challenges related to patient privacy and confidentiality including inference attacks. To address this, we present a semantic-based policy framework where linkage privacy detects attribute associations that can lead to inference disclosure issues. To illustrate the effectiveness of the approach, we present a case study exploring health data combining spatial, ethnicity and language information from several major on-going projects occurring across Australia. Compared with classic access control models, the results show that our proposal outperforms other approaches with regards to effectiveness, reliability and subsequent data utility

Privacy-Preserving Access Control in Electronic Health Record Linkage

Sharing aggregated electronic health records (EHRs) for integrated health care and public health studies is increasingly demanded. Patient privacy demands that anonymisation procedures are in place for data sharing. However traditional methods such as k-anonymity and its derivations are often over-generalizing resulting in lower data accuracy. To tackle this issue, we present the Semantic Linkage K-Anonymity (SLKA) approach supporting ongoing record linkages. We show how SLKA balances privacy and utility preservation through detecting risky combinations hidden in data releases