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Privacy Preserving Distributed Computation of Private Attributes for Collaborative Privacy Aware Usage Control Systems

Collaborative smart services provide functionalities which exploit data collected from different sources to provide benefits to a community of users. Such data, however, might be privacy sensitive and their disclosure has to be avoided. In this paper, we present a distributed multi-tier framework intended for smart-environment management, based on usage control for policy evaluation and enforcement on devices belonging to different collaborating entities. The proposed framework exploits secure multi-party computation to evaluate policy conditions without disclosing actual value of evaluated attributes, to preserve privacy. As reference example, a smart-grid use case is presented.
IEEE International Conference on Smart Computing (SMARTCOMP), Taormina, 2018

Autori IIT:

Tipo: Contributo in atti di convegno
Area di disciplina: Information Technology and Communication Systems

File: Internet of Things.pdf

Attività: Privacy dei dati personali multi soggetto