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2019 GTC San Jose
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S9802 - Context-Aware Network Mapping and Asset Classification

Session Speakers
Session Description

Traditional means of network mapping rely on expert knowledge, well-curated databases of network assets, and active internal scanning. Network maps are frequently out of date and often unable to provide the necessary ground-truth data to IT and security. We'll show how to leverage RAPIDS and GPU-Accelerated data science to learn a network mapping from passively generated logs. We'll discuss how we take this a step further by applying multiple machine learning analytics to the graph to infer asset ownership, classify assets and services on the network, and provide near real-time updates and alerts based on changes to the network topology. We'll explain how near real-time ingest and processing capabilities allow us to visualize the network quickly and provide context to the security professional in a timely manner.


Additional Information
Accelerated Data Science
Accelerated Data Science, Cyber Security
General
Intermediate technical
Talk
50 minutes
Session Schedule