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A Framework for Data Collection and Management for IoT

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Abstract: More and more personal devices and industrial systems have the capability to collect and transmit users’ data in order to provide services that are tailored to the specific needs of the customers. Such smart systems fall into the category of Internet of Things (IoT). However, in many cases, the data transmitted by such IoT devices includes sensitive information and users are faced with an all-or-nothing choice: either they adopt the proposed services and release their private data, or refrain from using services which could be beneficial but pose significant privacy risks. Unfortunately, encryption alone does not solve the problem, though techniques to counter these privacy risks are emerging (e.g., by using applications that alter, merge or bundle data to ensure they cannot be linked to a particular user). In this talk, we propose a general framework whereby users can not only specify how their data is managed but also restrict data collection from their connected devices. More precisely, we propose to use data collection policies to govern the transmission of data from IoT devices, coupled with policies to ensure that once the data has been transmitted, it is stored and shared in a secure way. To achieve this goal, we have designed a layered architecture for secure data collection, storage and management, with logical foundations that enable verification of policy properties.

Bio: Maribel Fernandez is a Professor of Computer Science in the Department of Informatics at King’s College London. She obtained her PhD in Paris in 1993, and her Habilitation in 2000 while she was a Maitre de conferences at the Ecole Normale Superieure (Paris). Her research interests include computation models, security, and the development of tools for the analysis and verification of complex systems. She uses rewriting-based techniques to analyse the dynamic behaviour, security and reliability of systems (from software applications to biochemical systems).

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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