Deanonymisation in Linked Data: A research roadmap

The objective of this roadmap is to summarise the state-of-the-art and to identify critical challenges for privacy in Linked Data. Our research particularly focuses on examining how the problem of data deanonymisation fits within the context of Linked Data. This draws attention to the fact that publishing data and linking them with other data (to achieve the Data Web vision) is also a significant threat to privacy. Interconnecting data with RDF from heterogeneous resources provides meaningful and valuable information in machine-understandable forms, but it may also offer fewer barriers for deanonymisation attacks to be achieved successfully, and potentially with full automation. Therefore, it is vital to keep both points of view into consideration; leveraging the Linked Data in the Web whilst also ensuring privacy when it is desired. In this paper, we aim to draw a research roadmap that will help to identify areas of significant concern, where the affordances of linked data align with the requirements for de-anonymisation and re-identification.

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