School of Computing


Digital Catapult Researcher in Residence

This Applied Project is focused on personal data that is continuously and, increasingly, autonoumously generated by people’s connected devices. Personal devices form the bulk of the IoT, as they become pervasive (wearables, smart homes, smart cars...) and increasingly connected to each other and to cloud infrastructure. The project addresses two issues concerning personal, streaming data flows. 1. Forwards traceability, from data generation to usages. Data generated by personal devices routinely becomes silently available to third parties, who are capable to use them to generate predictive models of individuals' habits. Mechanisms are needed to provide data owners with awareness and control over the flows of their data. 2. Backwards traceability, for forensic investigation of decisions made by machines. Increasingly, agents make autonomous decisions based on complex, automated exchanges of (personal) users data using M2M protocols. To provide accountability for those decisions, mechanisms are needed to create transparent, verifiable traces of the flows of information that lead to them.