Exploring presentation attack vulnerability and usability of face recognition systems
Abstract Commercial face recognition software intended for the use of access control is evaluated. Most of the systems are to be used with hand‐held devices (smartphones). The systems under test also contain three stationary systems designed to unlock doors or other secure entrance systems. While sp...
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| Format: | Article |
| Language: | English |
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Wiley
2021-03-01
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| Series: | IET Biometrics |
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| Online Access: | https://doi.org/10.1049/bme2.12015 |
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| _version_ | 1849686502866419712 |
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| author | Heinz Hofbauer Luca Debiasi Susanne Kränkl Andreas Uhl |
| author_facet | Heinz Hofbauer Luca Debiasi Susanne Kränkl Andreas Uhl |
| author_sort | Heinz Hofbauer |
| collection | DOAJ |
| description | Abstract Commercial face recognition software intended for the use of access control is evaluated. Most of the systems are to be used with hand‐held devices (smartphones). The systems under test also contain three stationary systems designed to unlock doors or other secure entrance systems. While specifics of the systems cannot be gone in‐depth under test (due to NDAs), the results of the evaluation of liveness detection (or presentation attack detection) with different complexity levels and template comparison performance are presented. The robustness against presentation attack is compares with the systems usability, and highlight where current commercial of the shelf systems (COTS) stand in that regard. The results focusing on the tradeoff between acceptance, linked with usability, and security are examined, which usually negatively impacts usability. A first extension of the attacks to systems using the NIR spectrum for imaging is also presented. This is mostly limited to stationary systems as they can include dedicated hardware with NIR capabilities. This is their main differentiation to most COTS systems running on smartphones, which do not rely on dedicated hardware. Though exceptions to this already exist for example in Apple devices. It is shown that most of the systems are not secure and not user friendly, having huge problems with difficult lighting conditions while only providing the most basic liveness or presentation attack detection capabilities. |
| format | Article |
| id | doaj-art-c003ecc5a218445ab2dfd0bf7b70f2d0 |
| institution | DOAJ |
| issn | 2047-4938 2047-4946 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj-art-c003ecc5a218445ab2dfd0bf7b70f2d02025-08-20T03:22:41ZengWileyIET Biometrics2047-49382047-49462021-03-0110221923210.1049/bme2.12015Exploring presentation attack vulnerability and usability of face recognition systemsHeinz Hofbauer0Luca Debiasi1Susanne Kränkl2Andreas Uhl3Multimedia Signal Processing and Security Lab Paris Lodron University of Salzburg Salzburg AustriaMultimedia Signal Processing and Security Lab Paris Lodron University of Salzburg Salzburg AustriaVeridos LLC. Munich GermanyMultimedia Signal Processing and Security Lab Paris Lodron University of Salzburg Salzburg AustriaAbstract Commercial face recognition software intended for the use of access control is evaluated. Most of the systems are to be used with hand‐held devices (smartphones). The systems under test also contain three stationary systems designed to unlock doors or other secure entrance systems. While specifics of the systems cannot be gone in‐depth under test (due to NDAs), the results of the evaluation of liveness detection (or presentation attack detection) with different complexity levels and template comparison performance are presented. The robustness against presentation attack is compares with the systems usability, and highlight where current commercial of the shelf systems (COTS) stand in that regard. The results focusing on the tradeoff between acceptance, linked with usability, and security are examined, which usually negatively impacts usability. A first extension of the attacks to systems using the NIR spectrum for imaging is also presented. This is mostly limited to stationary systems as they can include dedicated hardware with NIR capabilities. This is their main differentiation to most COTS systems running on smartphones, which do not rely on dedicated hardware. Though exceptions to this already exist for example in Apple devices. It is shown that most of the systems are not secure and not user friendly, having huge problems with difficult lighting conditions while only providing the most basic liveness or presentation attack detection capabilities.https://doi.org/10.1049/bme2.12015authorisationface recognitionsmart phones |
| spellingShingle | Heinz Hofbauer Luca Debiasi Susanne Kränkl Andreas Uhl Exploring presentation attack vulnerability and usability of face recognition systems IET Biometrics authorisation face recognition smart phones |
| title | Exploring presentation attack vulnerability and usability of face recognition systems |
| title_full | Exploring presentation attack vulnerability and usability of face recognition systems |
| title_fullStr | Exploring presentation attack vulnerability and usability of face recognition systems |
| title_full_unstemmed | Exploring presentation attack vulnerability and usability of face recognition systems |
| title_short | Exploring presentation attack vulnerability and usability of face recognition systems |
| title_sort | exploring presentation attack vulnerability and usability of face recognition systems |
| topic | authorisation face recognition smart phones |
| url | https://doi.org/10.1049/bme2.12015 |
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