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Event Details

MP Associates, Inc.
SUNDAY October 13, 9:00am - 1:00pm | Furman Hall 210
Machine Learning Security

Muhammad Shafique - Vienna Univ. of Technology, Vienna, Austria
Siddharth Garg - New York Univ., New York, NY
Brendan Dolan-Gavitt - New York Univ., New York, NY
Siddharth Garg - New York Univ., New York, NY

With the growing use of artificial intelligence (AI) and machine learning (ML) techniques in a wide range of domains, questions about their safety, security and privacy are of growing importance. A growing body of work suggests that modern AI and ML techniques are vulnerable to attack. Attacks include stealthy training data poisoning attacks, and so-called ``adversarial input perturbations” which have to been shown to be particularly pernicious for deep neural networks.

Further, as deep learning systems are often trained and executed in the cloud, concerns about the privacy of the user’s data and the IP rights of the model’s owner must be addressed. This tutorial will provide a comprehensive overview of a range of integrity and privacy attacks and emerging defense mechanisms.


Siddharth Garg received his Ph.D. degree in ECE from Carnegie Mellon University in 2009, and a B.Tech. degree in EE from the Indian Institute of Technology Madras. He joined NYU in Fall 2014 as an Assistant Professor. His general research interests are in computer engineering, and more particularly in secure, reliable and energy-efficient computing. In 2016, Siddharth was listed in Popular Science Magazine's annual list of "Brilliant 10" researchers. Siddharth has received the NSF CAREER Award (2015), and paper awards at IEEE Symposium on Security and Privacy (S&P) 2016 and USENIX Security Symposium 2013.

Muhammad Shafique is a full professor (Univ.Prof.) of Computer Architecture and Robust Energy-Efficient Technologies (CARE-Tech.) at the Embedded Computing Systems Group, Institute of Computer Engineering, Faculty of Informatics, Vienna University of Technology (TU Wien) since Nov. 2016. He received his Ph.D. in Computer Science from Karlsruhe Institute of Technology (KIT), Germany in Jan.2011. His research interests are in energy-efficient, dependable & fault-tolerant system design, hardware security, machine Learning and AI, and embedded systems. Dr. Shafique received 2015 ACM/SIGDA Outstanding New Faculty Award and several best paper awards and nominations at prestigious conferences like CODES+ISSS, DATE, DAC and ICCAD.

Brendan Dolan-Gavitt is currently an Assistant Professor in the Computer Science and Engineering Department at the NYU Tandon School of Engineering. His research interests include program analysis, virtualization security, machine learning security and embedded and cyber-physical systems. Currently, his research focuses on developing techniques to ease or automate the understanding of large, real-world software systems in order to develop novel defenses against attacks. He received his PhD from Georgia Tech in August 2014, and a B.A. in Mathematics and Computer Science from Wesleyan University in 2006.