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We present the SecureCloud EU Horizon 2020 project, whose goal is to enable new big data applications that use sensitive data in the cloud without compromising data security and privacy. For this, SecureCloud designs and develops a layered architecture that allows for (i) the secure creation and deployment of secure micro-services; (ii) the secure integration of individual micro-services to full-fledged big data applications; and (iii) the secure execution of these applications within untrusted cloud environments. To provide security guarantees, SecureCloud leverages novel security mechanisms present in recent commodity CPUs, in particular, Intel's Software Guard Extensions (SGX). SecureCloud applies this architecture to big data applications in the context of smart grids. We describe the SecureCloud approach, initial results, and considered use cases.

e growing adoption of distributed data processing frameworks in a wide diversity of application domains challenges end-to-end integration of properties like security, in particular when considering deployments in the context of large-scale clusters or multi-tenant Cloud infrastructures.is paper therefore introduces S S , a reactive middleware framework to deploy and process secure streams at scale. Its design combines the high-level reactive data ow programming paradigm with Intel®'s low-level so ware guard extensions (SGX) in order to guarantee privacy and integrity of the processed data. e experimental results of S S are promising: while o ering a uent scripting language based on L , our middleware delivers high processing throughput, thus enabling developers to implement secure processing pipelines in just few lines of code.