Streamlining the Big Data Landscape: Real World Network Security Usecase
By Sonali Parthasarathy
Accenture Technology Labs
sonali.parthasarathy AT accenture.com
In this paper, we introduce the concept of data acceleration and how it addresses the challenges of data movement, processing and interactivity. We propose a taxonomy to categorize the current Big Data technologies based on the challenges they address. We will demonstrate how these architecture categorizations have been applied to a real world use case. Using ArcSight data collected in the form of network security log files from a large North American network, we detect anomalous events and present the results using interactive visualizations. We describe our security use case technology stack which consists of data exploration tools (Tableau), real-time event processing and analytics tools (Kafka, Apama, GemFireXD, CDH5) and interactive visualizations (D3.js). Finally we will simplify the architecture decision-making process by prescribing the common architecture patterns.
[Big Data Architecture],[In-Memory Technologies],[Data Visualization], [Real-Time event processing], [Analytics]
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