| Paper ID | IFS-4.1 |
| Paper Title |
Highly Efficient Protection of Biometric Face Samples with Selective JPEG2000 Encryption |
| Authors |
Heinz Hofbauer, Paris Lodron University of Salzburg, Austria; Yoanna Martínez-Díaz, Advanced Technologies Application Center (CENATAV), Cuba; Simon Kirchgasser, Paris Lodron University of Salzburg, Austria; Heydi Méndez-Vázquez, Advanced Technologies Application Center (CENATAV), Cuba; Andreas Uhl, Paris Lodron University of Salzburg, Cuba |
| Session | IFS-4: Surveillance, Biometrics and Security |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation Time: | Wednesday, 09 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Information Forensics and Security: [BIO] Biometrics |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
When biometric databases grow larger, a security breach or leak can affect millions. In order to protect against such a threat, the use of encryption is a natural choice. However, a biometric identification attempt then requires the decryption of a potential huge database, making a traditional approach potentially unfeasible. The use of selective JPEG2000 encryption can reduce the encryption's computational load and enable a secure storage of biometric sample data. In this paper we will show that selective encryption of face biometric samples is secure. We analyze various encoding settings of JPEG2000, selective encryption parameters on the ``Labeled Faces in the Wild'' database and apply several traditional and deep learning based face recognition methods. |
