Trusted Biometrics under Spoofing Attacks
Description: The TABULA RASA project will address some of the issues of direct (spoofing) attacks to trusted biometric systems. This is an issue that needs to be addressed urgently because it has recently been shown that conventional biometric techniques, such as fingerprints and face, are vulnerable to direct (spoof) attacks.<br/>Direct attacks are performed by falsifying the biometric trait and then presenting this falsified information to the biometric system, one such example is to fool a fingerprint system by copying the fingerprint of another person and creating an artificial or gummy finger which can then be presented to the biometric system to falsely gain access. This issue effects not only companies in the high security field but also emerging small and medium sized enterprises (SMEs) that wish to sell biometric technologies in emerging fields.<br/>In particular the TABULA RASA project will:1. address the need for a draft set of standards to examine this problem,2. propose countermeasures such as combining biometric information from multiple sources,3. examine novel biometrics that may be inherently robust to direct attacks.<br/>The first issue of a draft set of standards will be addressed by analyzing the effectiveness of direct attacks to a range of biometrics, this will provide an insight as to how vulnerable the different biometric traits are to these attacks. The second issue of countermeasures will be explored in two lines, the first line of work proposes to combine multiple biometric traits to build a single system that is robust to direct attacks and the second line of work proposes to examine novel methods to perform liveness detection. Finally, novel biometrics which might be inherently robust to direct attacks, such as gait (the manner in which someone walks), vein or electro-physiological signals (such as the heart beat), will be explored to determine their advantages and limitations.
Funder: European Commission
Amount: €4,039,000
Funding type: research
Funder scheme: FP7 - CP
Start date: 2010-11-01
End date: 2014-04-30
Institution: FONDATION DE L'INSTITUT DE RECHERCHE IDIAP
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Funded outputs count: 19
Funder award ID: 257289
OpenAlex ID: G5306128564