RISS

The project investigated privacy requirements, developing a variety of novel techniques to capture and elicit user activity as part of field studies that involved real mobile applications. These techniques were used in conjunction with traditional methods such as focus group studies, interviewing and online questionnaires. We tracked user behavior to see how people interacted particularly with social networks, but also with monitoring location information relating to friends and family. These requirements were used to produce a privacy management framework that enables users to specify privacy preferences, to help visualize them, to learn from the user’s behaviour what their likely preferences are, and to enforce privacy policies. From the perspective of the Imperial research team, the emphasis of the work was on learning privacy policies which can automate the privacy related actions taken by users, by monitoring their past behavior. This was complemented by the work of the OU research team, who focussed on developing techniques for eliciting and analysing privacy requirements for mobile applications; conducting field studies to gain an in-depth understanding of users’ privacy concerns and to evaluate technologies for enhancing end-user privacy management.

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PRiMMA: Privacy Rights Management for Mobile ApplicationsRead More »

Policy-based management has been proposed in recent years as a suitable means for managing Quality of Service (QoS) in IP networks. Yet despite research projects, standardisation efforts, and substantial interest from industry, policy-based management is still not a reality. One of the reasons for the reticence to adopt this technology is that it is difficult to analyse policies to determine that they will actually work, given the capabilities of managed network devices, and to guarantee the stability of the network configuration, given that policies may have conflicts leading to unpredictable effects. This project aims to address the challenges of policy analysis, policy validation and policy refinement within the specific application domain of Quality of Service for IP networks. …

PAQMAN: Policy Analysis for Quality of service MANagementRead More »

Future e-science and e health applications will involve mobile users, possibly with on-body sensors interacting with a ubiquitous computing environment which detects their activity, current context and adapts accordingly. However, the promise of such ubiquitous computing environments will not be realised unless these systems can effectively disappear and for this they need to become autonomous by managingtheir own evolution and configuration changes without explicit user or administrator action. This project will develop the architecture, tools and techniques which permit these environments to become self-managing. To provide self-managment at varying levels (for individual devices, for simple body-areaor home-area networks, as well as large scale network infrastructures) we advocate the concept of a self managed cell (SMC) as the basic architecture pattern at both local and intergrated levels. We will define, prototype and evaluate architectures based on the SMC pattern and their use in e-health applications. To this end we will: define and implement the core SMC pattern in terms of the monitoring, service-discovery, context and policy-control services required for basic adaptation mechanisms, investigate how SMC’s can be dynamically structured into large structures and specialise SMC’s and their interactions for two e-health application scenarios.

This project was in Collaboration with Prof. Joe Sventek at the University of Glasgow