The 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. This paper therefore introduces SecureStreams, a reactive middleware framework to deploy and process secure streams at scale. Its design combines the high-level reactive dataflow programming paradigm with Intel®'s low-level software guard extensions (SGX) in order to guarantee privacy and integrity of the processed data. The experimental results of SecureStreams are promising: while offering a fluent scripting language based on Lua, our middleware delivers high processing throughput, thus enabling developers to implement secure processing pipelines in just few lines of code.
@cite_42 relies also on the JVM. This event processing system focuses on security by enforcing constraints on event flows between processing units. The event flow control is enforced using application-level virtualisation to separate processing units in a JVM.
@cite_42
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In finance and healthcare, event processing systems handle sensitive data on behalf of many clients. Guaranteeing information security in such systems is challenging because of their strict performance requirements in terms of high event throughput and low processing latency. We describe DEFCON, an event processing system that enforces constraints on event flows between event processing units. DEFCON uses a combination of static and runtime techniques for achieving light-weight isolation of event flows, while supporting efficient sharing of events. Our experimental evaluation in a financial data processing scenario shows that DEFCON can provide information security with significantly lower processing latency compared to a traditional approach.