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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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arXiv:1806.02075.pdf
(Preprint), 337KB

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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: https://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.