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GTC ON-DEMAND

Accelerated Data Science
Presentation
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Context-Aware Network Mapping and Asset Classification
Abstract:
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 Network maps are frequently out of date and often unable to provide the necessary ground-truth data to IT and security.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.
 
Topics:
Accelerated Data Science, Cyber Security
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9802
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