  In this research project, we investigate an alternative to the standard
cloud-centralized data architecture. Specifically, we aim to leave part of the
application data under the control of the individual data owners in
decentralized personal data stores. Our primary goal is to increase data
minimization, i. e., enabling more sensitive personal data to be under the
control of its owners while providing a straightforward and efficient framework
to design architectures that allow applications to run and data to be analyzed.
To serve this purpose, the centralized part of the schema contains aggregating
views over this decentralized data. We propose to design a declarative language
that extends SQL, for architects to specify different kinds of tables and views
at the schema level, along with sensitive columns and their minimum granularity
level of their aggregations. Local updates need to be reflected in the
centralized views while ensuring privacy throughout intermediate calculations;
for this we pursue the integration of distributed materialized view maintenance
and multi-party computation (MPC) techniques. We finally aim to implement this
system, where the personal data stores could either live in mobile devices or
encrypted cloud storage, in order to evaluate its performance properties.

Databases