BlueSky: Combining Task Planning and Activity-Centric Access Control for Assistive Humanoid Robots

In the not too distant future, assistive humanoid robots will provide versatile assistance for coping with everyday life. In their interactions with humans, not only safety, but also security and privacy issues need to be considered. In this Blue Sky paper, we therefore argue that it is time to bring task planning and execution as a well-established field of robotics with access and usage control in the field of security and privacy closer together. In particular, the recently proposed activity-based view on access and usage control provides a promising approach to bridge the gap between these two perspectives. We argue that humanoid robots provide for specific challenges due to their task-universality and their use in both, private and public spaces. Furthermore, they are socially connected to various parties and require policy creation at runtime due to learning. We contribute first attempts on the architecture and enforcement layer as well as on joint modeling, and discuss challenges and a research roadmap also for the policy and objectives layer. We conclude that the underlying combination of decentralized systems\u27 and smart environments\u27 research aspects provides for a rich source of challenges that need to be addressed on the road to deployment

ADAPT: Approach to Develop context-Aware solutions for Personalised asthma managemenT

The creation of sensors allowing the collection of a high amount of data has been possible thanks to the evolution of information and communication technology. These data must be properly interpreted to deliver meaningful information and services. Context-aware reasoning plays an important role in this task, and it is considered as a hot topic to study in the development of solutions that can be categorised under the scope of Intelligent Environments. This research work studies the use of context-aware reasoning as a tool to provide support in the asthma management process. The contribution of this study is presented as the Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT), which can be used as a guideline to create solutions supporting asthma management in a personalised way. ADAPT proposes context-aware reasoning as an appropriate tool to achieve the personalisation that is required to address the heterogeneity of asthma. This heterogeneity makes people with asthma have different triggers provoking their exacerbations and to experience different symptoms when their exacerbations occur, which is considered as the most challenging characteristic of the condition when it comes to implementing asthma treatments. ADAPT context dimensions are the main contribution of the research work as they directly address the heterogeneity of asthma management by allowing the development of preventive and reactive features that can be customised depending on the characteristics of a person with asthma. The approach also provides support to people not knowing their triggers properly through case-based reasoning, and includes virtual assistant as a complementing technology supporting asthma management. The comprehensive nature of ADAPT motivates the study of the interaction between context-aware reasoning and case-based reasoning in Intelligent Environments, which is also reported as a key contribution of the research work. The inclusion of people with asthma, carers and experts in respiratory conditions in the experiments of the research project was possible to achieve thanks to the collaboration formed with Asthma UK

Data privacy threat modelling for autonomous systems: a survey from the GDPR’s perspective

Artificial Intelligence-based applications have been increasingly deployed in every field of life including smart homes, smart cities, healthcare services, and autonomous systems where personal data is collected across heterogeneous sources and processed using ”black-box” algorithms in opaque centralised servers. As a consequence, preserving the data privacy and security of these applications is of utmost importance. In this respect, a modelling technique for identifying potential data privacy threats and specifying countermeasures to mitigate the related vulnerabilities in such AI-based systems plays a significant role in preserving and securing personal data. Various threat modelling techniques have been proposed such as STRIDE, LINDDUN, and PASTA but none of them is sufficient to model the data privacy threats in autonomous systems. Furthermore, they are not designed to model compliance with data protection legislation like the EU/UK General Data Protection Regulation (GDPR), which is fundamental to protecting data owners' privacy as well as to preventing personal data from potential privacy-related attacks. In this article, we survey the existing threat modelling techniques for data privacy threats in autonomous systems and then analyse such techniques from the viewpoint of GDPR compliance. Following the analysis, We employ STRIDE and LINDDUN in autonomous cars, a specific use-case of autonomous systems, to scrutinise the challenges and gaps of the existing techniques when modelling data privacy threats. Prospective research directions for refining data privacy threats & GDPR-compliance modelling techniques for autonomous systems are also presented

University of San Diego News Print Media Coverage 2004.11

Printed clippings housed in folders with a table of contents arranged by topic.https://digital.sandiego.edu/print-media/1022/thumbnail.jp

Cardiovascular Genetics: Candidate Gene, Candidate Pathway and Whole Genome Analyses

This thesis consists of three different studies with the common aim of identifying novel genetic influences on cardiovascular risk in hypertensive individuals. A candidate gene study was conducted to assess the association of genetic variation in the (pro)renin receptor ((P)RR), a recently-discovered member of the renin-angiotensin system, with blood pressure (BP) levels in two healthy Irish populations. We found a number of single nucleotide polymorphisms (SNPs) to be consistently associated with decreased BP (P In two candidate pathway studies, we assessed genetic variation across genes in two biological pathways likely to play a role in BP regulation; ion channels (91 genes) and neurotransmitters (188 genes), for association with BP in two healthy Irish populations. We found that SNPs in a chloride channel gene, in a potassium channel gene and in a gene encoding a glutamate receptor precursor, were associated with increased BP with experiment-wide statistical significance. Together, these targeted association studies have identified novel genes which have not been previously implicated in BP control, provide new insights into the pathophysiology of BP control, and may represent novel drug targets and/or pharmacogenetic markers. Finally, a genome wide association study investigated the genetic determinants of two prostanoids, thromboxane (TxA2) and prostacyclin (PGI2), both of which play important roles in platelet and vascular homeostasis. In -800 Caucasian hypertensive subjects, 6 loci were statistically associated with levels of TxA2/ PGI2 at experiment-wide level. These associations were strongly influenced by use of aspirin, which inhibits production of these prostanoids. The genetic determinants of TxA2 and PGI2have not been examined before and the variants identified in this study may be novel predictors of atherothrombotic risk and help to inform the use of anti-platelet agents such as aspirin