Towards a Security-Aware Deployment of Data Streaming Applications in Fog Computing

Emerging fog and edge computing environments enable the analysis of Big Data collected from devices (e.g., IoT sensors) with reduced latency compared to cloud-based solutions. In particular, many applications deal with continuous data flows in latency-sensitive domains (e.g., healthcare monitoring), where Data Stream Processing (DSP) systems represent a popular solution. However, the highly heterogeneous nature of fog/edge platforms poses several challenges for efficiently deploying DSP applications, including security and privacy issues. As data streams flow through public networks and are possibly processed within multi-tenant computing platforms, new metrics must be considered for deployment, accounting for security and privacy related concerns, besides traditionally adopted performance and cost aspects. In this chapter, we present the most relevant existing solutions for deploying DSP applications in fog/edge environments, discussing—in particular—how they address security and privacy concerns. Then, we present Security-aware DSP Placement (SDP), a formulation of the optimal deployment problem for DSP applications in fog/edge environments. Specifically, we introduce security-related application requirements in addition to non-functional ones, and show how the resolution of SDP allows us to trade-off cost and performance with privacy and data integrity objectives.