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Paper

Extended Diffix

MPS-Authors
/persons/resource/persons144528

Francis,  Paul
Group P. Francis, Max Planck Institute for Software Systems, Max Planck Society;

/persons/resource/persons231542

Munz,  Reinhard
Group P. Francis, Max Planck Institute for Software Systems, Max Planck Society;

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Fulltext (public)

arXiv:1806.02075.pdf
(Preprint), 337KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Francis, P., Probst-Eide, S., Obrok, P., Berneanu, C., Juric, S., & Munz, R. (2018). Extended Diffix. Retrieved from http://arxiv.org/abs/1806.02075.


Cite as: http://hdl.handle.net/21.11116/0000-0003-37D4-0
Abstract
A longstanding open problem is that of how to get high quality statistics through direct queries to databases containing information about individuals without revealing information specific to those individuals. Diffix is a new framework for anonymous database query that adds noise based on the filter conditions in the query. A previous paper described Diffix for a simplified query semantics. This paper extends that description to include a wide variety of common features found in SQL. It describes attacks associated with various features, and the anonymization steps used to defend against those attacks. This paper describes the version of Diffix used for bounty program sponsored by Aircloak starting December 2017.