Luke joined the group as a Research Associate after having completed a PhD at Imperial College London under the supervision of Dr Alessandra Russo. Luke focuses on machine learning techniques and is working on techniques for dealing with partially trusted sources of information in particular in crowdsourcing scenarios. Luke is now a lecturer at University College London.
Refining policies from high level goals to enforceable specifications in asemi-automated and principled ways remains one of the most significant challenges in policy based systems. We have on two occasions attempted to tackle this challenges in collaboration with Dr Alessandra Russo at Imperial, Dr Arosha Bandara at the Open University and Dr Jorge Lobo at IBM. The first attempt wast done during the Dr Bandara’s PhD thesis. …
The Self-Managed Cell is an architectural pattern for building autonomous pervasive systems. It was developed in collaboration with Prof. Joe Sventek at the University of Glasgow, and with my colleagues Dr. Narnaker Dulay and Prof. Morris Sloman at Imperial College.
Enrico designed a framework for secure dissemination of information in partially disconnected environments as part of the Consequence project. This was in particular applied to information exchanges between first responder organisations in crisis management scenario. His work also investigated the protection of derived data. After successfully completing his PhD under the supervision of Dr Emil Lupu, Enrico took a position with Morgan Stanley. He is now a Senior Software engineer at Microsoft.
Alberto did his PhD thesis under the supervision of Dr Emil Lupu and contributed significantly to our work on the Self Managed Cells. In particular, his work focussed on means of realising autonomous interactions, compositions and federations of cells in a recursive fashion. After completing his PhD, Alberto became a Research Associate at Lancaster University. He is now an Associate Professor at the Federal University of Rio Grande do Sul (UFRGS). His web page is here.
Ponder2 combines a general-purpose, distributed object management system with a Domain Service, Obligation Policy Interpreter, Command Interpreter and Authorisation Enforcement. The Domain Service provides an hierarchical structure for managing objects. The Obligation Policy Interpreter handles Event, Condition, Action rules (ECA). The Command Interpreter accepts a set of commands, compiled from a high-level language called PonderTalk, via a number of communications interfaces which may perform invocations on a ManagedObjectregistered in the Domain Service. The Authorisation Enforcement caters for both positive and negative authorisation policies, provides the ability to specify fine grained authorisations for every object and implements domain nesting algorithms for conflict resolution. …
Dr. Kevin Twidle has been a long time member and associate of the Distributed Software Engineering Group at Imperial College. In recent years he has been the main designer and implementer of the Ponder2 software, which was used within Imperial and by outside organisations in a broad range of contexts including for the management of Body Sensor Networks for eHealth, Autonomous Vehicles, Heterogeneous Networks, Mobile Workflows and Distributed Authorisation Systems. He is now an IT consultant based in France but working world wide.
Sye-Loong obtained his PhD in 2005 under the supervision of Dr. Emil Lupu. He then worked with us as a Research Associate until 2008 when he joined Philips Research in Eindhoven. In 2013, Sye-Loong left industry to return to academia and was appointed as an Assistant Professor with the University of Glasgow in Singapore. His current web page is here.
“Consequence” was a collaborative research project partly funded by the European Commission, which ran between 2008 and 2011. The project built a comprehensive framework for controlled dissemination of information based on Data Sharing Agreements and a combination of technologies based on rights management and usage control policies. The framework was demonstrated within the context of sharing large scale scientific data and also for controlled sharing of information between first responder organisations in crisis management scenarios. More details, videos, papers and project deliverable are available from the Consequence web site.
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The project aims to facilitate data sharing in cloud environments by providing end-to-end data centric security from the client to the cloud based on the (semi-)automated enforcement ofData Sharing Agreements. These agreements may reflect legal, contractual or user defined preferences, which may be conflicting and thus an appropriate balance and model for their enforcement must be found.
The project aims to study privacy management by investigating how individuals learn and benefit from their membership of social or functional groups, and how such learning can be automated and incorporated in modern mobile and ubiquitous technologies that increasingly pervade society. The project will focus on addressing the privacy concerns of individuals in the context of their use of pervasive technologies, such as Smartphones and Clouds and aims to contribute in three research areas: (1) engineering of adaptive systems that guide their users to manage their privacy; (2) the development of logic-based machine learning techniques to alleviate the cognitive and physical load of personalising users’ privacy requirements; and (3) empirical investigation of the privacy behaviour of and in groups, in the context of both collaboration and conflict. This is a joint project with The Open University and the University of Exeter, funded by the EPSRC (Grant No EP/K033425/1). At Imperial the project is led by Dr Alessandra Russo.
How will Big Data affect innovation, growth and well-being in the UK economy? By Big Data we mean very large or complex datasets that are constantly accumulating in society because of the dramatically increased ability to sense, capture, store and analyse information about social, economic, or scientific phenomena. We anticipate that Big Data and associated analytics may ultimately transform how societies and communities view themselves, and how governments, large corporations, and entrepreneurial startup companies relate to those populations. Therefore it is essential to consider how Big Data might contribute to economic growth and generate opportunities for innovation for UK companies. …
The Intel ICRI in Sustainable Connected Cities is a joint project between Intel, Imperial College London, and University College London. Its activities are concerned with how to enhance the social, economic and environmental well being of cities by advancing compute, communication and social constructs to deliver innovations in system architecture, algorithms and societal participation.
Our work within the initiative concerns mainly the security and resilience of Wireless Sensor Networks.
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.
2013, Funded by EIT ICT Labs
Partners: Inria (Lead), Alcatel Lucent, Cap Digital, Imperial College, SAP, KTH, LiquidMedia
Crowd-sourcing, if used properly, is a very powerful instrument to collect, enrich and exploit data and knowledge in Digital Cities. The aim of this project is to build, deploy and assess novel services on crowd-sourcing platforms that integrate both data capture facilities and core services enabling the turstworthiness of the crowd to be dynamically evaluated, offering rich workflow modeling for hybrid processing and ensuring privacy guarantees on crowdsourced data.