Abstract: Despite expanding regulations, surveillance tech and Face ID deployments continue to grow geometrically. Countries such as the US, China, and the UK are leading the way, while the rest of the world is not far behind. Biometric data and algorithms are at the epicenter of a perfect storm, as rapid technological advances meet rising privacy concerns. At the one end, identification technology like face recognition can provide consumers both convenience and secure authentication. At the other end, biometric databases and infrastructure have become attractive targets for hackers. In a new twist, open source AI tools are now available that can help malicious actors manipulate face and voice data to create deep fakes. These fakes can be weaponized by rogue nation states for disinformation campaigns - to destabilize financial markets or manipulate elections.
Our panel will take a data-centric perspective on these topics. We will review the state of the art in face recognition technology and discuss where biometrics is headed. We will look at novel ways to secure biometric data, such as homomorphic encryption and leveraging the blockchain. And we will explore the role that deep learning is playing in both improving identification accuracy as well in fake news and cybersecurity.
Bio: Hyrum Anderson is the Chief Scientist at Endgame, where he leads research on detecting adversaries and their tools using machine learning. Prior to joining Endgame he conducted information security and situational awareness research as a researcher at FireEye, Mandiant, Sandia National Laboratories and MIT Lincoln Laboratory. He received his PhD in Electrical Engineering (signal and image processing + machine learning) from the University of Washington and BS/MS degrees from BYU. Research interests include adversarial machine learning, large-scale malware classification, and early time-series classification.
Chief Scientist | EndGame
advanced-w19 | beginner-w19 | deep-learning-w19 | intermediate-w19 | open-source-w19 | tutorials-w19