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Evolving Perspectives on Adversarial Robustness for Deep Neural Networks

March 9 (2022) @ 3:00 pm - 4:00 pm

Despite their tangible impact on a wide range of real world applications, deep neural networks are known to be vulnerable to numerous attacks, including inference time attacks based on adversarial perturbations, as well as training time attacks such as backdoors. The security community has done extensive work in recent years to explore both attacks and defenses. In this talk, I will first discuss some of our projects at UChicago SAND Lab covering both sides of the struggle between attacks and defenses, including recent work on honeypot defenses (CCS 2020) and physical domain poison attacks (CVPR 2021).

Unfortunately, our experiences in these projects has only reaffirmed the inevitable cat and mouse nature of attacks and defenses. Looking forward, I believe we must go beyond the current focus on attacking & defending single static DNN models, and to bring more pragmatic perspectives to improving robustness for deployed ML systems. To this end, I will present some of our early work on digital forensics for DNNs, and outline some future challenges in this new space.

Zoom Meeting link: https://newcastleuniversity.zoom.us/j/81973967294?pwd=Wk52RUpDSis1SDl1NmJOV2dEcGRadz09

Meeting ID: 819 7396 7294
Passcode: 025103

Youtube Live Streaming: https://youtu.be/rdisOGCvXYY


March 9 (2022)
3:00 pm - 4:00 pm
Seminar Tags:


Ben Zhao (University of Chicago)

Ben Zhao is Neubauer Professor of Computer Science at University of Chicago. Prior to joining UChicago, he held the position of Professor of Computer Science at UC Santa Barbara. He completed his Ph.D. at U.C. Berkeley (2004), and B.S. from Yale (1997). He is a Fellow of the ACM, and a recipient of the NSF CAREER award, MIT Technology Review's TR-35 Award (Young Innovators Under 35), ComputerWorld Magazine's Top 40 Technology Innovators award, IEEE ITC Early Career Award, and Google Faculty awards. His work has been covered by media outlets such as New York Times, Boston Globe, LA Times, MIT Tech Review, Wall Street Journal, Forbes, Fortune, CNBC, MSNBC, New Scientist, and Slashdot. He has published extensively in areas of security and privacy, machine learning, networking, and HCI. He served as TPC (co)chair for the World Wide Web conference (WWW 2016) and ACM Internet Measurement Conference (IMC 2018). He also serves on the steering committee for HotNets, and was general co-chair for HotNets 2020.

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