Keynote Speakers

Richard Rinkens (EC, DG Home) - How the Entry Exit System will impact Schengen


The European Commission adopted a new proposal for the Entry Exit System (EES) after an intense period of analysis and real-world testing. The new proposal is based on multi-modal biometrics combining 4-fingerprints and a good quality facial-image taken live. The no-longer existing Registered Traveller Programme will be replaced by automation for all regular travellers, using self-service kiosks, smart-phones and eGates. The Entry Exit System will improve the quality and efficiency of controls at external borders while helping MS deal with increasing traveller's flows without an increase of the number of border guards. One of the main objectives is the identification of overstayers and to enable subsequent evidence based visa policy making. The EES will seriously reinfoce internal security and fight against terrorism.



After implementing the Biometric Matching System (BMS) for the Visa Information System (VIS), Richard worked on a variety of strategic ideas and concepts involving biometrics and identity management such as the Smart Borders package. In parallel to preparing the implementation of a SISII AFIS, he is focussing on Digitalisation of Home Affairs, creating policy on border-control, biometrics and identity management. After the Schengen Masterlist project to enable electronic authentication of travel documents, he is now also focussing on creating Stronger and Smarter Information Systems for Borders and Security. Richard has an academic background in electronics, informatics and artificial intelligence.



Arun Ross (Michigan State University, U.S.) - To Identify or to De-identify? Privacy in Biometrics


By its very definition, biometrics seeks to “recognize" individuals based on their biological attributes. Therefore, the issue of personal privacy is often legitimately raised in the context of biometric systems. Concomitant questions include: (a) Can additional information about an individual be automatically gleaned from biometric data? (b) Can biometrics be used to surreptitiously track an individual? (c) Can multiple biometric databases be linked to develop a more complete profile of an individual? (d) Who owns the biometric data collected from an individual, and how long should the biometric data be retained in an identity management system?  

In the first part of this talk, we will discuss methods by which biographical (e.g., gender from fingerprints), anatomical (e.g., crypts in iris), sensor (e.g., type of device used to image a certain fingerprint), and contextual (e.g., intensity of ambient lighting during iris image acquisition) information can be gleaned from biometric data. While the resultant information can be used to improve person recognition performance in the framework of “soft” biometrics or forensics, the extraction of such information can be deemed to violate privacy. So in the second part of the talk, we will discuss ways by which privacy can be accorded to stored biometric data. The proposed methods will rely on the principles of visual cryptography and signal mixing to generate biometric templates that can suppress some of the additional information about a person that is resident in the biometric data. We will report experimental results discussing the efficacy of these methods. The talk will conclude by pointing out that privacy enhancing technologies 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 (MSU) and the Director of the i-PRoBe Lab. Prior to joining MSU in 2013, he was a faculty member at West Virginia University (WVU) from 2003 to 2012. He also served as the Assistant Site Director of the NSF Center for Identification Technology and Research (CITeR) between 2010 and 2012.

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 (YBIA), 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. 

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. 



Davide Maltoni (Università di Bologna, Italy) - Predicting Large-scale Fingerprint Recognition Accuracy


Predicting accuracy of biometric systems is a very difficult problem. Statistical modeling techniques often require to make assumptions on data distributions that we cannot validate in practice. A different approach is running fingerprint recognition algorithms on large datasets of synthetic data. However, we have to face two problems: i) ensure that synthetic data well approximate real data; ii) running huge amount of fingerprint comparisons in a reasonable time. Interesting results have been recently achieved on these topics within the Fidelity EU project, thus making possible to make predictions in line with known results from evaluations on real data such as FPVTE2012 and UIDAI project.


Davide Maltoni is a Full Professor at University of Bologna (Italy), and chair of the Cesena Unit of the Computer Science Department. In 1998, he received his PhD in Computer Science and Engineering from DEIS, University of Bologna. He currently teaches “Computer Architectures” and “Pattern Recognition”. Davide Maltoni’s research interests are in the area of Pattern Recognition and Computer Vision. In particular, he is active in the field of Biometric Systems.

Davide Maltoni is co-director of the Biometric Systems Laboratory (BioLab), which is internationally known for its research and publications in the field. Several original techniques have been proposed by BioLab team for fingerprint feature extraction, matching and classification, for hand shape verification, for face location and recognition and for performance evaluation of biometric systems. In particular, BioLab developed and published the first algorithm able to meet the FBI error requirements for automatic fingerprint classification and developed SFinGe, the first effective method for generating realistic synthetic fingerprint databases. He holds three patents on Fingerprint Recognition. In cooperation with Prof. A.K.Jain from Michigan State University and Prof. J.Wayman from San Josè University, BioLab organized the well-known Fingerprint Verification Competitions: FVC2000, FVC2002, FVC2004, FVC2006, and FvcOnGoing. Davide Maltoni is co-author of the “Handbook of Fingerprint Recognition” published by Springer, New York, 2003, which received the prestigious 2003 PSP award for the “Computer Science” category given by the Association of American Publishers; a second version of the handbook has been published by Springer in 2009.

Davide Maltoni has been associate editor of the journals: “IEEE Transaction on Transactions on Information Forensics and Security” and “Pattern Recognition”; he is currently Associate Editor of "IEEE Transaction on Pattern Analysis and Machine Intelligence". He co-organized the Biometric Authentication workshop (BioAW 2004), the Automatic Identification workshop (AutoID 2007), the International Conference on Biometric Autentication (ICB 2009) and joined the program committee of a number of conferences on pattern recognition and on biometrics. He is an IEEE member and IAPR Fellow