Michigan State University, US
Keynote Speech Title:
What Else Does Your Biometric Data Reveal?
Biometric systems utilize physical and behavioral traits such as fingerprints, face, iris, voice and gait, to automatically recognize a person. The word “recognize” is derived from the Latin verb “recognoscere”, which means “know again” or “recall to mind”. While the biometric data acquired from an individual is expected to be used only for recognition purposes, it is possible to glean additional information from this data thereby leading to function creep. For example, it has been shown that attributes related to a person’s gender, age, race, health, etc. can be automatically deduced from the biometric data. While these attributes – sometimes referred to as “soft” biometrics – can be used to enhance the recognition accuracy of a biometric system, they can also be deemed to compromise the privacy of an individual.
In this talk, we will discuss some of the methods that have been developed in the literature to extract additional information about an individual from the biometric data. Next, we will present methods that can impart privacy to the biometric data of an individual. We will conclude the talk by pointing out that privacy enhancing schemes can be judiciously used by biometric systems to ensure that the benefits of biometrics are not undermined by privacy concerns.
Arun Ross is a Professor in the Department of Computer Science and Engineering at Michigan State University. Prior to joining the MSU Faculty in January 2013, he was with West Virginia University (WVU) as an Assistant Professor from 2003 to 2008 and as an Associate Professor from 2008 to 2012. He also served as the Assistant Site Director of the NSF Center for Identification Technology and Research between 2010 and 2012. His research interests include pattern recognition, classifier fusion, machine learning, computer vision, and biometrics. He is the coauthor of the textbook “Introduction to Biometrics” and the monograph “Handbook of Multibiometrics”, and the co-editor of “Handbook of Biometrics”. He is a recipient of the IAPR JK Aggarwal Prize, the IAPR Young Biometrics Investigator Award, the NSF CAREER Award, and was an invited speaker at the Frontiers of Science Symposium organized by the National Academy of Sciences in November 2006. He is also a recipient of the 2005 Biennial Pattern Recognition Journal Best Paper Award and the Five Year Highly Cited BTAS 2009 Paper Award.
Arun served as a panelist at a counter-terrorism event that was organized by the United Nations Counter-Terrorism Committee (CTC) at the UN Headquarters in May 2013. He was an Associate Editor of IEEE Transactions on Information Forensics and Security (2009 – 2013), and IEEE Transactions on Image Processing (2008 – 2013). He currently serves as Associate Editor of IEEE Transactions on Circuits and Systems for Video Technology, Senior Area Editor of IEEE Transactions on Image Processing, Area Editor of the Computer Vision and Image Understanding Journal, Associate Editor of the Image and Vision Computing Journal, and Chair of the IAPR TC4 on Biometrics.
EiC of IEEE Transactions on Information Forensics and Security
Keynote Speech Title
Copying with the enemy: Multimedia forensics in adversarial conditions
Multimedia forensics is an emerging discipline aiming at recovering information about the history of a multimedia document based on the subtle traces left within the document during media acquisition and processing. Most applications of multimedia forensics are thought to operate under adversarial conditions, like in the course of police investigations, as a proof in a court of law, as a mean for copyright protection and many others. For this reason, the study of counter-forensics and anti-counter-forensic techniques has gained more and more popularity.
Despite such an interest, most works in this area still use a naive approach to define the security of multimedia forensic tool. In this talk, we illustrate the need for a rigorous formal framework to define multimedia forensics security and discuss the main ingredients that such a framework should consist of. We then present a taxonomy of threat models specifically thought to deal with multimedia forensics peculiarities and we illustrate the possible use of such threat models together with game theory to study the impact that the presence of an adversary has on the achievable performance in some multimedia forensics problems.
Mauro Barni received the Electronics Engineering degree from the University of Florence, in 1991, and the Ph.D. degree in informatics and telecommunications in 1995. He has carried out his research activity for over 20 years, first with the Department of Electronics and Telecommunication, University of Florence, and then with the Department of Information Engineering and Mathematics, University of Siena, where he works as a Full Professor.
During the last two decades, he has been studying the application of image processing techniques to copyight protection and authentication of multimedia, and the possibility of processing signals that have been previously encrypted without decrypting them (digital watermarking, multimedia forensics, and signal processing in the encrypted domain). Lately, he has been working on theoretical and practical aspects of adversarial signal processing.
He has participated in several national and European research projects on diverse topics, including computer vision, multimedia signal processing, remote sensing, digital watermarking, and IPR protection. He has authored or co-authored about 300 papers published in international journals and conference proceedings, and is the author of five patents in the field of digital watermarking and image authentication. He has co-authored the book Watermarking Systems Engineering: Enabling Digital Assets Security and Other Applications (Dekker Inc., 2004).
He was the Funding Editor of the EURASIP Journal on Information Security. He is the current Editor-in-Chief of the IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY. He was the Chairman of the IEEE Information Forensic and Security Technical Committee from 2010 to 2011 and the Technical Program co-Chair of ICASSP 2014. He was appointed as a DL of the IEEE SPS from 2013 to 2014. He is a member of EURASIP and a fellow of IEEE. He was the recipient of the 2016 Individual Technical Achievement of EURASIP.