IEEE Signal Processing Magazine Special Issue on Biometric Security and Privacy

Guest Editors

Nicholas Evans - EURECOM, France 

Andrew Teoh Beng Jin - Yonsei University, Seoul, South Korea

Sébastien Marcel - Idiap Research Institute, Switzerland 

Arun Ross - Michigan State University, USA 

 

 

Biometrics is the science of recognising individuals based on their physical and behavioural traits such as face, fingerprints, iris, voice, gait and signature. A typical biometric system may be viewed as a pattern recognition system which utilises advanced signal processing schemes to compare and match biometric data. The past decade has seen a rapid increase in biometrics research as well as the deployment of large-scale biometric solutions in civilian and law enforcement applications. Since the biometric data of an individual can be viewed as being personal and sensitive, issues related to biometric security and privacy have been raised. These include (a) spoofing, where an adversary presents a falsified biometric trait to the system with the intention of masquerading as another person; (b) evasion, where a person attempts to obfuscate or modify a biometric trait in order to avoid being detected by the system; (c) database alteration, where the templates stored in a database are modified in order to undermine system integrity; and (d) template compromise, where the stored biometric data is perused or stolen and exploited for illegitimate means. The goal of this special issue is to highlight recent advances made in the field of biometrics security and privacy protection. A number of signal processing methods have been developed to analyse the vulnerability of biometric systems and design solutions to mitigate their impact. At the same time, privacy-preserving constructs have been developed by signal processing researchers in order to ensure that stored and/or transmitted biometric data is adequately protected so as to prevent their use for purposes beyond those intended. The special issue will bring together the latest work in biometric security and privacy protection, with an emphasis on tutorial and review-style articles.

 

Download the Call for Papers