Detecting Cyber Threats with Unsupervised Learning
Offer
Enterprises are faced with an incredibly vast network of data to protect. The massive scale, dimensionality, and heterogeneity of user application data require an adaptive and granular approach to detect malicious actions. Join this webinar where we will demonstrate NVIDIA Morpheus, an open-source AI framework, lets cybersecurity developers use machine learning to adaptively learn role, user, account behavior independently to identify deviations from typical activity.
By joining this webinar, you'll learn:
- How user application data can be used for cybersecurity
- About the data science tools available to help monitor every user and machine across your network
- How to set up a pipeline to detect malicious user activity using AI
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speaker
Gorkem Batmaz
Senior Data Scientist, NVIDIAGorkem Batmaz is a senior data scientist on the Morpheus team at NVIDIA. His focus is on applying GPU accelerated high-performance analytics to solve cybersecurity challenges. He developed machine learning-natural language processing-based predictive maintenance, phishing-domain generation algorithm (DGA)-malware detection, asset classification, anomaly detection and periodicity detection solutions that are open source. Prior to NVIDIA Morpheus, Gorkem worked on the cybersecurity team for NVIDIA's autonomous cars division. Before joining NVIDIA in 2011, he worked at Motorola and Alcatel-Lucent. He holds an MS in engineering and technology management and a BS in electrical & electronics engineering from Bogazici University.
Shyam Kumar
Global BD Lead, HPC & Autonomous Vehicles, AWSShyam is on the High Performance Computing (HPC) specialist organization at Amazon Web Services (AWS) and leads the Business Development activities and Go-To-Market (GTM) strategy for the Autonomous Vehicles (AV) segment. In this role, he helps Automotive OEM's, Tier-1's and Startups leverage the elasticity, scale and technical capabilities of AWS to innovate faster and accelerate their AV development process. Shyam has a Master's degree in Mechanical Systems Engineering, and has held various technical, business development, and sales leadership roles in multiple industries over the course of his career with a focus on engineering simulations and scientific computing.
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