Abstract
For the first time, the feasibility of creating morphed samples for attacking vascular biometrics is investigated, in particular finger vein recognition schemes are addressed. A conducted vulnerability analysis reveals that (i) the extent of vulnerability, (ii) the type of most vulnerable recognition scheme, and (iii) the preferred way to determine the best morph sample for a given target sample depends on the employed sensor. Digital morphs represent a significant threat as vulnerability in terms of IAPMR is often found to be > 0.8 or > 0.6 (in sensor dependent manner). Physical artefacts created from these morphs lead to clearly lower vulnerability (with IAPMR ≤ 0.25), however, this has to be attributed to the low quality of the artefacts (and is expected be increase for better artefact quality).
Original language | English |
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Title of host publication | 2021 IEEE International Joint Conference on Biometrics (IJCB) |
Publisher | IEEE |
Pages | 1-7 |
Number of pages | 7 |
ISBN (Electronic) | 9781665437806 |
ISBN (Print) | 9781665437806 |
DOIs | |
Publication status | Published - 7 Aug 2021 |
Event | 2021 IEEE International Joint Conference on Biometrics (IJCB) - Shenzhen, China Duration: 4 Aug 2021 → 7 Aug 2021 |
Publication series
Name | 2021 IEEE International Joint Conference on Biometrics, IJCB 2021 |
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Conference
Conference | 2021 IEEE International Joint Conference on Biometrics (IJCB) |
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Period | 4/08/21 → 7/08/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
Fields of Science and Technology Classification 2012
- 102 Computer Sciences