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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.

Users of online services such as messaging, code hosting and collaborative document editing expect the services to uphold the integrity of their data. Despite providers' best efforts, data corruption still occurs, but at present service integrity violations are excluded from SLAs. For providers to include such violations as part of SLAs, the competing requirements of clients and providers must be satisfied. Clients need the ability to independently identify and prove service integrity violations to claim compensation. At the same time, providers must be able to refute spurious claims.We describe LibSEAL, a SEcure Audit Library for Internet services that creates a non-repudiable audit log of service operations and checks invariants to discover violations of service integrity. LibSEAL is a drop-in replacement for TLS libraries used by services, and thus observes and logs all service requests and responses. It runs inside a trusted execution environment, such as Intel SGX, to protect the integrity of the audit log. Logs are stored using an embedded relational database, permitting service invariant violations to be discovered using simple SQL queries. We evaluate LibSEAL with three popular online services (Git, ownCloud and Dropbox) and demonstrate that it is effective in discovering integrity violations, while reducing throughput by at most 14%.