Paper 2023/481
A Framework for UC Secure Privacy Preserving Biometric Authentication using Efficient Functional Encryption
Abstract
Despite its popularity, password based authentication is susceptible to various kinds of attacks, such as online or offline dictionary attacks. Employing biometric credentials in the authentication process can strengthen the provided security guarantees, but raises significant privacy concerns. This is mainly due to the inherent variability of biometric readings that prevents us from simply applying a standard hash function to them. In this paper we first propose an ideal functionality for modeling secure, privacy preserving biometric based two-factor authentication in the framework of universal composability (UC). The functionality is of independent interest and can be used to analyze other two-factor authentication protocols. We then present a generic protocol for biometric based two-factor authentication and prove its security (relative to our proposed functionality) in the UC framework. The first factor in our protocol is the possession of a device that stores the required secret keys and the second factor is the user's biometric template. Our construction can be instantiated with function hiding functional encryption, which computes for example the distance of the encrypted templates or the predicate indicating whether the templates are close enough. Our contribution can be split into three parts: - We model privacy preserving biometric based two-factor authentication as an ideal functionality in the UC framework. To the best of our knowledge, this is the first description of an ideal functionality for biometric based two-factor authentication in the UC framework. - We propose a general protocol that uses functional encryption and prove that it UC-realizes our ideal functionality. - We show how to instantiate our framework with efficient, state of the art inner-product functional encryption. This allows the computation of the Euclidean distance, Hamming distance or cosine similarity between encrypted biometric templates. In order to show its practicality, we implemented our protocol and evaluated its performance.
Metadata
- Available format(s)
- Category
- Cryptographic protocols
- Publication info
- Preprint.
- Keywords
- cryptographic protocolsbiometric authenticationprivacy preserving computationuniversal composability
- Contact author(s)
-
johannes ernst @ unisg ch
katerina mitrokotsa @ unisg ch - History
- 2023-04-05: approved
- 2023-04-03: received
- See all versions
- Short URL
- https://ia.cr/2023/481
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2023/481, author = {Johannes Ernst and Aikaterini Mitrokotsa}, title = {A Framework for {UC} Secure Privacy Preserving Biometric Authentication using Efficient Functional Encryption}, howpublished = {Cryptology {ePrint} Archive, Paper 2023/481}, year = {2023}, url = {https://eprint.iacr.org/2023/481} }