dc.creator | Arjona, Rosario | es |
dc.creator | Baturone Castillo, María Iluminada | es |
dc.date.accessioned | 2022-09-21T09:54:33Z | |
dc.date.available | 2022-09-21T09:54:33Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Arjona, R. y Baturone Castillo, M.I. (2020). A post-quantum biometric template protection scheme based on Learning Parity with Noise (LPN) commitments. IEEE Access, 8, 182355. https://doi.org/10.1109/ACCESS.2020.3028703. | |
dc.identifier.issn | 2169-3536 | es |
dc.identifier.uri | https://hdl.handle.net/11441/137253 | |
dc.description.abstract | Biometric recognition has the potential to authenticate individuals by an intrinsic link between
the individual and their physical, physiological and/or behavioral characteristics. This leads a higher security
level than the authentication solely based on knowledge or possession. One of the reasons why biometrics is
not completely accepted is the lack of trust in the storage of biometric templates in external servers. Biometric
data are sensitive data which should be protected as is contemplated in the data protection regulation of many
countries. In this work, we propose the use of biometric Learning Parity With Noise (LPN) commitments as
template protection scheme. To the best of our knowledge, this is the first proposal for biometric template
protection based on the LPN problem (that is, the difficulty of decoding random linear codes), which offers
post-quantum security. Biometric features are compared in the protected domain. Irreversibility, revocability,
and unlinkability properties are satisfied as well as resistance to False Acceptance Rate (FAR), crossmatching, Stolen Token, and similarity-based attacks. A recognition accuracy with a 0% FAR is achieved,
because user-specific secret keys are employed, and the False Rejection Ratio (FRR) can be adjusted
depending on a threshold to preserve the accuracy of the unprotected scheme in the Stolen Token scenario.
A good performance in terms of execution time, template storage and operation complexity is obtained for
security levels at least of 80 bits. The proposed scheme is employed in a dual-factor authentication protocol
from the literature to illustrate how it provides security using authentication and database (cloud) servers
that can be malicious. The proposed LPN-based protected scheme can be applied to any biometric trait
represented by binary features and any matching score based on Hamming or Jaccard distances. In particular,
experimental results are included of a practical finger vein-based recognition system implemented in Matlab. | es |
dc.format | application/pdf | es |
dc.format.extent | 11 p. | es |
dc.language.iso | eng | es |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | es |
dc.relation.ispartof | IEEE Access, 8, 182355. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | biometric template protection | es |
dc.subject | post-quantum security | es |
dc.subject | LPN commitments | es |
dc.subject | dual-factor authentication | es |
dc.subject | authentication protocol | es |
dc.subject | finger veins | es |
dc.title | A post-quantum biometric template protection scheme based on Learning Parity with Noise (LPN) commitments | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Electrónica y Electromagnetismo | es |
dc.relation.publisherversion | https://dx.doi.org/10.1109/ACCESS.2020.3028703 | es |
dc.identifier.doi | 10.1109/ACCESS.2020.3028703 | es |
dc.journaltitle | IEEE Access | es |
dc.publication.volumen | 8 | es |
dc.publication.initialPage | 182355 | es |