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Tuesday, August 4 • 18:00 - 18:55
Making & Breaking Machine Learning Anomaly Detectors in Real Life

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Machine learning techniques used in network intrusion detection are susceptible to 'model poisoning' by attackers. We dissect this attack and analyze some proposals for how to circumvent these attacks, then consider specific use cases of how machine learning and anomaly detection can be used in the web security context.

avatar for Clarence Chio

Clarence Chio

Software Engineer, Shape Security
Clarence recently graduated with a B.S. and M.S. in Computer Science from Stanford University, specializing in data mining and artificial intelligence. He currently works at Shape Security, a startup in Silicon Valley building a product that protects its customers from malicious bot... Read More →

Tuesday August 4, 2015 18:00 - 18:55 PDT
Ground Truth Florentine F

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