TY - GEN
T1 - MasterPrint Attack Resistance
T2 - 10th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2019
AU - Roy, Aditi
AU - Memon, Nasir
AU - Ross, Arun
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under Grants 1618750 and 1617466.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - User authentication based on fingerprints is vulnerable to dictionary attacks. Recent research has demonstrated the possibility of generating a small number of 'MasterPrints' that can fortuitously match the fingerprints of a large number of identities. The problem is particularly exacerbated for partial prints such as those used in smartphones. Such systems often store multiple templates per user (e.g., multiple impressions of a single finger) to compensate for the limited size of the sensor, variation in finger placement, and other types of intra-class variations. The presence of multiple templates, however, increases their chances of matching against a MasterPrint thereby compromising security. This paper presents a novel technique to perform template selection in such a way that the chance of MasterPrint attack gets reduced. Experiments conducted using a commercial fingerprint matcher on two datasets indicate that the proposed approach can be effective against MasterPrint attacks whilst retaining verification performance.
AB - User authentication based on fingerprints is vulnerable to dictionary attacks. Recent research has demonstrated the possibility of generating a small number of 'MasterPrints' that can fortuitously match the fingerprints of a large number of identities. The problem is particularly exacerbated for partial prints such as those used in smartphones. Such systems often store multiple templates per user (e.g., multiple impressions of a single finger) to compensate for the limited size of the sensor, variation in finger placement, and other types of intra-class variations. The presence of multiple templates, however, increases their chances of matching against a MasterPrint thereby compromising security. This paper presents a novel technique to perform template selection in such a way that the chance of MasterPrint attack gets reduced. Experiments conducted using a commercial fingerprint matcher on two datasets indicate that the proposed approach can be effective against MasterPrint attacks whilst retaining verification performance.
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U2 - 10.1109/BTAS46853.2019.9186010
DO - 10.1109/BTAS46853.2019.9186010
M3 - Conference contribution
AN - SCOPUS:85092316517
T3 - 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems, BTAS 2019
BT - 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems, BTAS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 23 September 2019 through 26 September 2019
ER -