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Australian Information Security Management Conference, This paper proposes 9 core elements of information security accountability in the area of cloud computing. The core elements were determined via a series of 18 case studies with Omani government organisations that were actively using and/or providing cloud computing. 36 interviews were conducted and then analysed using a grounded theory methodology As a result of the analysis, responsibility, transparency, assurance, remediation, accountability support environment, flexible change process, collaboration, mechanisms and commitment to external criteria. The research also found that the emphasis on specific core elements is context-dependent and that there was considerable variation in emphasis amongst the case study organisations.

Australian Information Security Management Conference, This paper presents an analysis that arose from a comprehensive review of the academic and professional literature of two areas – information security management systems (ISMS) and information resources – and their relationship with information security. It analyzes the role of ISMS in protecting an organization’s information environment and infrastructure. It has identified four key areas that strongly influence the safety of information resources: cloud computing; social media/networking; mobility; and information management/big data. Commonly referred to as ‘new forces’, these four aspects are all growing exponentially and are not easily controlled by IT. Another key finding of the paper is that organizations aiming to protect their information resources need to adapt their ISMS in an environment where these new forces have exposed them to a range of external entities and influences.

"Cambodia", [PDF Acrobat File] in Ian Storey and Lee Poh Onn, eds. Regional Outlook: Southeast Asia 2009-2010, Institute of Southeast Asian Studies, Singapore, January 2009.

Background: There are few available methods for qualitatively evaluating patients with primary progressive aphasia (PPA). Commonly adopted approaches are time-consuming, of limited accuracy, or designed to assess different patient populations. This paper introduces a new clinical test - the Mini Linguistic State Examination (MLSE) - which was designed uniquely to enable a clinician to assess and subclassify both classical and mixed presentations of PPA. The adoption of a novel assessment method (error classification) greatly amplifies the clinical information that can be derived from a set of standard linguistic tasks and allows a five-dimensional profile to be defined. Methods: Fifty-four patients and 30 matched controls were recruited. Five domains of language competence (motor speech, phonology, semantics, syntax, and working memory) were assessed using a sequence of 11 distinct linguistic assays. A random forest classification was used to assess the diagnostic accuracy for predicting PPA subtypes and create a decision tree as a guide to clinical classification. Findings: The random forest prediction model was 96% accurate overall (92% for logopenic variant, 93% for semantic variant, and 98% for non-fluent variant PPA). The derived decision tree produced a correct classification of 91% of participants whose data were not included in the training set. Interpretation: The MLSE is a new cognitive test incorporating a novel and powerful, yet straightforward, approach to scoring. Rigorous assessment of its diagnostic accuracy confirmed excellent matching of PPA syndromes to clinical gold standard diagnoses. Adoption of the MLSE by clinicians will have a decisive impact on the consistency and uniformity with which patients can be described clinically. It will also facilitate screening for cohort-based research, including future therapeutic trials, and is suitable for describing, quantifying and monitoring language deficits in other brain disorders. Funding Information: The research was funded by a Medical Research Council Research Grant award (Ref MR/N025881/1) to PG, MLR JR, KP and SC. Additional support was provided through grants from the MRC (UAG051 and G101400), Wellcome Trust (103838) and ERC (GAP: 670428), and through funding awarded to the National Institute for Health Research Cambridge Biomedical Research Centre and to the MRC CBU (MC_UU_00005/18). Declaration of Interests: JBR reports consultancy unrelated to the work with Biogen, UCB, Asceneuron and Althira; and receipt of research grants, unrelated to this work, from Janssen, AZ-Medimmune, and Lilly. The other authors declare no conflicts of interest. Ethics Approval Statement: Written informed consent was provided by all participants. The study protocol was reviewed and approved by the London (Chelsea) Research Ethics Committee [Ref. 16/LO/1735].