IEEE SPS Distinguished Lecture: Adversarial attacks on image classifiers
Images of people and scenes we share online reveal information about personal choices and preferences, which can be automatically inferred by classifiers. To prevent privacy violations and to protect the visual content from unwanted automatic inferences, we show how to exploit the vulnerability of classifiers to adversarial attacks to craft adversarial perturbations that maintain (and even improve) image quality. However, these perturbations may be ineffective against classifiers that were not seen during the generation of the perturbation or against defences that use re-quantization or image compression. To address these limitations, I will present a series of adversarial attacks designed to protect visual content against classifiers. I will discuss how to craft perturbations based on randomised ensembles to make them robust to defences, on image semantics to selectively modify colours within chosen ranges that are perceived as natural by humans, and on perturbations that enhance image details.
Date and Time
- Date: 29 Oct 2020
- Time: 10:00 AM to 11:00 AM
- All times are US/Central
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Professor Andrea Cavallaro of Queen Mary University of London, U
Professor of Multimedia Signal Processing and the founding Director of the Centre for Intelligent Sensing at Queen Mary University of London, UK
Andrea Cavallaro is Professor of Multimedia Signal Processing and the founding Director of the Centre for Intelligent Sensing at Queen Mary University of London, UK. He is Fellow of the International Association for Pattern Recognition (IAPR) and Turing Fellow at the Alan Turing Institute, the UK National Institute for Data Science and Artificial Intelligence. He received his Ph.D. in Electrical Engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, in 2002. He was a Research Fellow with British Telecommunications (BT) in 2004/2005 and was awarded the Royal Academy of Engineering Teaching Prize in 2007; three student paper awards on target tracking and perceptually sensitive coding at IEEE ICASSP in 2005, 2007 and 2009; and the best paper award at IEEE AVSS 2009. Prof. Cavallaro is Editor-in-Chief of Signal Processing: Image Communication; Chair of the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee; an IEEE Signal Processing Society Distinguished Lecturer; and an elected member of the IEEE Video Signal Processing and Communication Technical Committee. He is Senior Area Editor for the IEEE Transactions on Image Processing and Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology. He is a past Area Editor for the IEEE Signal Processing Magazine (2012-2014) and past Associate Editor for the IEEE Transactions on Image Processing (2011-2015), IEEE Transactions on Signal Processing (2009-2011), IEEE Transactions on Multimedia (2009-2010), IEEE Signal Processing Magazine (2008-2011) and IEEE Multimedia. He is a past elected member of the IEEE Multimedia Signal Processing Technical Committee and past chair of the Awards committee of the IEEE Signal Processing Society, Image, Video, and Multidimensional Signal Processing Technical Committee. Prof. Cavallaro has published over 270 journal and conference papers, one monograph on Video tracking (2011, Wiley) and three edited books: Multi-camera networks (2009, Elsevier); Analysis, retrieval and delivery of multimedia content (2012, Springer); and Intelligent multimedia surveillance (2013, Springer).