Joshua Patterson is the Director of Applied Solutions Engineering at NVIDIA and a former White House Presidential Innovation Fellow. Prior to NVIDIA, Josh worked with leading experts across public sector, private sector, and academia to build a next generation cyber defense platform. His current passions are graph analytics, machine learning, and GPU data acceleration. Josh also loves storytelling with data, and creating interactive data visualizations. Josh holds a B.A. in economics from the University of North Carolina at Chapel Hill and an M.A. in economics from the University of South Carolina Moore School of Business.
Analyzing vast amounts of enterprise cyber security data to find threats is hard. Cyber threat detection is also a continuous task, and because of financial pressure, companies have to find optimized solutions for this volume of data. We'll discuss the evolution of big data architectures used for cyber defense and how GPUs are allowing enterprises to do better threat detection more efficiently. We'll discuss (1) briefly the evolution of traditional platforms to lambda architectures with new approaches like Apache Kudu to ultimately GPU-accelerated solutions; (2) current GPU-accelerated database, analysis, and visualization technologies (such as Kinetica and Graphistry), and discuss the problems they solve; (3) the need to move beyond traditional table-based data-stores to graphs for more advanced data explorations, analytics, and visualization; and (4) the latest advances in GPU-accelerated graph analytics and their importance all for improved cyber threat detection.