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How DataVisor Optimizes its AWS Stack to Protect 4B+ Online Accounts from Fraud

By David Ting September 10, 2018

Photo of David Ting

about David Ting
With over 20 years of leadership experience at leading technology companies such as Yahoo, NetEase, and IGN. On the technology front, David has held key executive positions at Yahoo, IBM, IGN, AltaVista and is a big believer in combining cutting-edge innovation with scalability, simplicity, and quick time-to-market. He holds 6 patents and won 2 IBM Outstanding Achievement awards and AltaVista Employee of the Year.

DataVisor’s David Ting, VP of Engineering, shares how DataVisor optimizes AWS to protect over 4B accounts with Unsupervised Machine Learning. David discusses how modern, coordinated fraud has rendered existing fraud detection solutions ineffective, and why DataVisor’s platform offers the next level of detection by combining unsupervised machine learning algorithms with big data technology. Next, he covers how DataVisor has optimized its AWS instance to be able to efficiently analyze billions of events in real-time.

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Session Abstract:

Today’s cyber criminals are growing more sophisticated than ever. They use large armies of fraudulent user accounts to conduct widely distributed attacks against consumer-facing online services. Join us as David Ting, VP of engineering at DataVisor, shares how his company uses AWS technology to power the next generation of online fraud detection and protect some of the largest internet properties in the world.

Interested Unsupervised Machine Learning and Big Data?

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