Math, Motion, and Machine Learning: Implicit Authentication in the Real World

  • When Dec 03, 2019 from 06:00 PM to 07:00 PM (America/Los_Angeles / UTC-800)
  • Where Gates Building, Room 174
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Math, Motion, and Machine Learning: Implicit Authentication in the Real World - John Whaley, CEO and Founder of UnifyID, Stanford CS Alum 

Tuesday 12/3, 6-7PM
Gates Building, Room 174
 

How do you identify people? What is it that makes you, you? Certain aspects of human behavior can be as unique and as hard to spoof as a fingerprint. The way you walk, the way you move, the places you go, and your little idiosyncrasies have the promise of being more convenient and more secure than other forms of authentication like passwords or biometrics. But there are significant practical challenges in building a system that can authenticate you to >99% accuracy with just a few seconds of passive sensor readings while still maintaining user privacy. It requires lots of advanced math, signal processing, machine learning, tricky engineering, and re-thinking existing security paradigms.

Come hear about our experience in building such a platform and a glimpse into the future of authentication.

About UnifyID:

UnifyID, a rapidly growing startup located in Downtown Redwood City, that uses human behavioral data (like gait) to build authentication software. UnifyID has raised $23.4 million from top firms like NEA and Andreessen Horowitz.

 

Dinner will be served for the first 15 to RSVP and guarantee attendance! 

RSVP: https://forms.gle/9EA3HTkCvMH44HpP7