Mutually Assured Destruction and the Impending AI Apocalypse

David Evans, University of Virginia

Abstract: 

The history of security includes a long series of arms races, where a new technology emerges and is subsequently developed and exploited by both defenders and attackers. Over the past few years, "Artificial Intelligence" has re-emerged as a potentially transformative technology, and deep learning in particular has produced a barrage of amazing results. We are in the very early stages of understanding the potential of this technology in security, but more worryingly, seeing how it may be exploited by malicious individuals and powerful organizations. In this talk, I'll look at what lessons might be learned from previous security arms races, consider how asymmetries in AI may be exploited by attackers and defenders, touch on some recent work in adversarial machine learning, and hopefully help progress-loving Luddites figure out how to survive in a world overrun by AI doppelgängers, GAN gangs, and gibbon-impersonating pandas.

David Evans, University of Virginia

David Evans is a Professor of Computer Science at the University of Virginia where he leads the Security Research Group. He is the author of an open computer science textbook and a children's book on combinatorics and computability. He won the Outstanding Faculty Award from the State Council of Higher Education for Virginia, and was Program Co-Chair for the 24th ACM Conference on Computer and Communications Security (CCS 2017) and the 30th (2009) and 31st (2010) IEEE Symposia on Security and Privacy. He has SB, SM and PhD degrees in Computer Science from MIT and has been a faculty member at the University of Virginia since 1999.

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BibTeX
@conference {222135,
author = {David Evans},
title = {Mutually Assured Destruction and the Impending {AI} Apocalypse},
year = {2018},
address = {Baltimore, MD},
publisher = {{USENIX} Association},
}