Security Assessment of Selectively Encrypted Visual Data: Iris Recognition on Protected Samples

Martin Rieger; Jutta Hämmerle-Uhl; Andreas Uhl

doi:10.1109/ICIP42928.2021.9506294

Security Assessment of Selectively Encrypted Visual Data: Iris Recognition on Protected Samples

Martin Rieger, Jutta Hämmerle-Uhl, Andreas Uhl

Artificial Intelligence and Human Interfaces

Publikation: Beitrag in Buch/Bericht/Konferenzband/Gesetzeskommentar › Konferenzbeitrag › Peer-reviewed

Abstract

Security assessment of partially encrypted visual data is known to be difficult. We show that iris recognition performance on encrypted sample data turns out to be a good predictor for protection strength of encryption schemes for visual data, in particular in settings where image structure and intelligibility is preserved to some extent. This is of particular interest, as common image quality metrics used for this task exhibit specifically poor prediction quality in this setting.

Originalsprache	Englisch
Titel	2021 IEEE International Conference on Image Processing (ICIP)
Herausgeber (Verlag)	IEEE
Seiten	3008-3012
Seitenumfang	5
ISBN (Print)	978-1-6654-3102-6
DOIs	https://doi.org/10.1109/ICIP42928.2021.9506294
Publikationsstatus	Veröffentlicht - 22 Sept. 2021
Veranstaltung	2021 IEEE International Conference on Image Processing (ICIP) - Anchorage, AK, USA Dauer: 19 Sept. 2021 → 22 Sept. 2021

Konferenz

Konferenz	2021 IEEE International Conference on Image Processing (ICIP)
Zeitraum	19/09/21 → 22/09/21

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10.1109/ICIP42928.2021.9506294

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9506294

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