Prof. Julian Fierrez
Universidad Autónoma de Madrid (Spain)
Securing our Identity: from Biometric Anti-Spoofing to DeepFakes Detection
In the last decade we have witnessed extraordinary advances in technologies aimed at managing and securing our identity for online and mobile applications including e-commerce, e-health, e-banking, e-learning, and others. This has been enabled by a rapidly evolving mobile market, with smartphones now having impressive computation capabilities and many audiovisual and biometric-specific sensors capable of acquiring high-quality face images, voice, fingerprints, and other biometric information. This context has nurtured the development of biometric technology that can represent in a very distinctive way our individual identity. These advances in biometric identity have come, at the same time, with growing risks. The information secured by biometric models in our smartphones and other computing platforms are nowadays more valuable than ever, and therefore a growing number of attacks are being conducted seeking big returns by faking our biometric identities. This keynote will summarize the main advances in biometric security conducted in the last decade aimed at evaluating the security of biometric systems against presentation attacks (aka spoofing attacks). Additionally, and as a natural evolution of the mentioned security aspects of biometric identities, we will discuss a topic of growing interest nowadays: facial image manipulation techniques, including DeepFakes, and ways to detect such manipulations. These manipulation techniques, boosted by recent advances in deep learning, can nowadays be used for biometric impersonation in very harmful ways. Both lines of research (biometric anti-spoofing and facial manipulation detection) in a sense have the same purpose: in an interconnected world where we interact more than ever via digital representations of ourselves including in many cases biometric information, there is a growing need for securing our digital identities against a growing army of attackers and attacking methods.
Julian FIERREZ received the MSc and the PhD degrees in telecommunications engineering from Universidad Politecnica de Madrid, Spain, in 2001 and 2006, respectively. Since 2004 he has been at Universidad Autonoma de Madrid, where he is Associate Professor since 2010. From 2007 to 2009 he was a visiting researcher at Michigan State University in the USA under a Marie Curie fellowship. His research is on signal and image processing, AI fundamentals and applications, HCI, forensics, and biometrics for security and human behavior analysis. He is actively involved in large EU projects in these topics (e.g., BIOSECURE, TABULA RASA and BEAT in the past; now IDEA-FAST, PRIMA and TRESPASS-ETN). Since 2016 he has been Associate Editor for Elsevier's Information Fusion and IEEE Trans. on Information Forensics and Security, and since 2018 also for IEEE Trans. on Image Processing. He has been General Chair of the IAPR Iberoamerican Congress on Pattern Recognition (CIARP 2018) and the Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2019). Since 2020 he is a member of the ELLIS Society. Prof. Fierrez has received best papers awards at AVBPA, ICB, IJCB, ICPR, ICPRS, and Pattern Recognition Letters. He is also recipient of a number of world-class research distinctions, including: EBF European Biometric Industry Award 2006, EURASIP Best PhD Award 2012, Medal in the Young Researcher Awards 2015 by the Spanish Royal Academy of Engineering, and the Miguel Catalan Award to the Best Researcher under 40 in the Community of Madrid in the general area of Science and Technology. In 2017 he was also awarded the IAPR Young Biometrics Investigator Award, given to a single researcher worldwide every two years under the age of 40, whose research work has had a major impact in biometrics. [http://biometrics.eps.uam.es/]