MasterPrint Attack Resistance: A Maximum Cover Based Approach for Automatic Fingerprint Template Selection

Aditi Roy, Nasir Memon, Arun Ross

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publication2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems, BTAS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728115221
DOIs
StatePublished - Sep 2019
Event10th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2019 - Tampa, United States
Duration: Sep 23 2019Sep 26 2019

Publication series

Name2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems, BTAS 2019

Conference

Conference10th IEEE International Conference on Biometrics Theory, Applications and Systems, BTAS 2019
CountryUnited States
CityTampa
Period9/23/199/26/19

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software
  • Instrumentation

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