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CrazyFaces: Unassisted Circumvention of Watchlist Face Identification

Damer, Naser and Wainakh, Yaza and Boller, Viola and Berken, Sven von den and Terhörst, Philipp and Braun, Andreas and Kuijper, Arjan (2018):
CrazyFaces: Unassisted Circumvention of Watchlist Face Identification.
In: 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS), Los Angeles, California, October 22-25, DOI: 10.1109/BTAS.2018.8698557, [Online-Edition: https://doi.org/10.1109/BTAS.2018.8698557],
[Conference or Workshop Item]

Abstract

Once upon a time, there was a blacklisted criminal who usually avoided appearing in public. He was surfing the Web, when he noticed, what had to be a targeted advertisement announcing a concert of his favorite band. The concert was in a near town, and the only way to get there was by train. He was worried, because he heard in the news about the new face identification system installed at the train station. From his last stay with the police, he remembers that they took these special face images with the white background. He thought about what can he do to avoid being identified and an idea popped in his mind “what if I can make a crazy-face, as the kids call it, to make my face look different? What do I exactly have to do? And will it work?”. He called his childhood geeky friend and asked him if he can build him a face recognition application he can tinker with. The geeky friend was always interested in such small projects where he can use open-source resources and didn’t really care about the goal, as usual. The criminal tested the application and played around, trying to figure out how can he make a crazy-face that won’t be identified as himself. On the day of the concert, he took off to the train station with some doubt in his mind and fear in his soul. To know what happened next, you should read the rest of this paper.

Item Type: Conference or Workshop Item
Erschienen: 2018
Creators: Damer, Naser and Wainakh, Yaza and Boller, Viola and Berken, Sven von den and Terhörst, Philipp and Braun, Andreas and Kuijper, Arjan
Title: CrazyFaces: Unassisted Circumvention of Watchlist Face Identification
Language: English
Abstract:

Once upon a time, there was a blacklisted criminal who usually avoided appearing in public. He was surfing the Web, when he noticed, what had to be a targeted advertisement announcing a concert of his favorite band. The concert was in a near town, and the only way to get there was by train. He was worried, because he heard in the news about the new face identification system installed at the train station. From his last stay with the police, he remembers that they took these special face images with the white background. He thought about what can he do to avoid being identified and an idea popped in his mind “what if I can make a crazy-face, as the kids call it, to make my face look different? What do I exactly have to do? And will it work?”. He called his childhood geeky friend and asked him if he can build him a face recognition application he can tinker with. The geeky friend was always interested in such small projects where he can use open-source resources and didn’t really care about the goal, as usual. The criminal tested the application and played around, trying to figure out how can he make a crazy-face that won’t be identified as himself. On the day of the concert, he took off to the train station with some doubt in his mind and fear in his soul. To know what happened next, you should read the rest of this paper.

Uncontrolled Keywords: Biometrics, Face recognition, Spoofing attacks, Deep learning, CRISP
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Fraunhofer IGD
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Event Location: Los Angeles, California
Event Dates: October 22-25
Date Deposited: 06 May 2019 06:35
DOI: 10.1109/BTAS.2018.8698557
Official URL: https://doi.org/10.1109/BTAS.2018.8698557
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