  In the Internet of Things and smart environments data, collected from
distributed sensors, is typically stored and processed by a central middleware.
This allows applications to query the data they need for providing further
services. However, centralization of data causes several privacy threats: The
middleware becomes a third party which has to be trusted, linkage and
correlation of data from different context becomes possible and data subject
lose control over their data.
  Hence, other approaches than centralized processing should be considered.
Here, Secure Multiparty Computation is a promising candidate for secure and
privacy-preserving computation happening close to the sources of the data.
  In order to make SMC fit for application in these contexts, we extend SMC to
act as a service: We provide elements which allow third parties to query
computed data from a group of peers performing SMC. Furthermore, we establish
fine-granular access control on the level of individual data queries, yielding
data protection of the computed results. By adding measures to inform data
sources about requests and the usage of their data, we show how a fully
privacy-preserving service can be built on the foundation of SMC.
