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2019 GTC San Jose
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S9803 - Using the Data You Collect: Accelerating Cybersecurity Applications with RAPIDS

Session Speakers
Session Description

Network defense and cybersecurity applications traditionally rely on heuristics and signatures to protect networks and detect anomalies. Large companies may generate over 10TB of data daily, spread across different sensors and heterogenous data types. The difficulty of providing timely ingest, feature engineering, feature exploration, and model generation has made signature-based detection the only option. We'll show how to use RAPIDS and GPU acceleration to overcome these obstacles. We'll walk through data engineering steps involving large amounts of heterogeneous data (both source and format) and explore how GPUs can accelerate feature exploration and hyperparameter selection. This enables more in-house data scientists and information security experts to use internally collected data to generate predictive models for anomaly detection rather than rely on signature-based detection.


Additional Information
Accelerated Data Science
Accelerated Data Science, Cyber Security
Defense, General, IT Services
All technical
Tutorial
1h 20m
Session Schedule