Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme
Bian, Weixin; Gope, Prosanta; Cheng, Yongqiang; Li, Qingde
Dr Yongqiang Cheng Y.Cheng@hull.ac.uk
Dr Qingde Li Q.Li@hull.ac.uk
The fingerprint has long been used as one of the most important biological features in the field of biometrics. It is person-specific and remain identical though out one’s lifetime. Physically uncloneable functions (PUFs) have been used in authentication protocols due to the unique physical feature of it. In this paper, we take full advantage of the inherent security features of user’s fingerprint biometrics and PUFs to design a new user authentication and key agreement scheme, namely Bio-AKA, which meets the desired security characteristics. To protect the privacy and strengthen the security of biometric data and to improve the robustness of the proposed scheme, the fuzzy extractor is employed. The scheme proposed in the paper can protect user’s anonymity without the use of password and allow mutual authentication with key agreement. The experimental results show superior robustness and the simplicity of our proposed scheme has been validated via our performance and security analysis. The scheme can be an ideal candidate for real life applications that requires remote user authentication.
|Journal Article Type||Article|
|Journal||Future Generation Computer Systems|
|Peer Reviewed||Peer Reviewed|
|APA6 Citation||Bian, W., Gope, P., Cheng, Y., & Li, Q. (2020). Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme. Future generations computer systems : FGCS, 109, 45-55. https://doi.org/10.1016/j.future.2020.03.034|
|Keywords||Mutual authentication; Key agreement; Physical unclonable functions; Fuzzy extractor; Biometric security and privacy|
|Additional Information||This article is maintained by: Elsevier; Article Title: Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme; Journal Title: Future Generation Computer Systems; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.future.2020.03.034; Content Type: article; Copyright: © 2020 Elsevier B.V. All rights reserved.|
This file is under embargo until Mar 20, 2021 due to copyright reasons.
Contact Y.Cheng@hull.ac.uk to request a copy for personal use.
You might also like
Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes
Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions
High precision implicit modeling for patient-specific coronary arteries
A Survey of the Methods on Fingerprint Orientation Field Estimation
Towards additive manufacturing oriented geometric modeling using implicit functions