Abstract
With the development of Internet technology and the change of network environment, it is particularly important to ensure the security and privacy of biometrics in the process of biometrics authentication. In this regard, we propose a novel identity authentication protocol based on cancelable biometric and Physical Unclonable Function (PUF) which uses the properties of PUF to generate the cancelable biometric and adds it to the complete authentication protocol, so as to realize the two-way authentication between the user and the server. Our authentication protocol makes full use of the characteristics of what users bring in and who users are, overcomes the shortcomings of the traditional key-based protocol, and connecting with the supervised learning algorithm SVM and elliptic curve Pedersen commitment, construct an effective, unique and cancelable biometric identity to replace original biometrics, thus improving the security and privacy protection of the biometrics template. At the same time, we analyze the accuracy of classification algorithms, the revocability and unlinkability of templates through experiments, which further ensures the security and legitimacy of the authentication protocol.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kumar, N.: Cancelable biometrics: a comprehensive survey. Artif. Intell. Rev. 53(11), 3403–34462 (2020)
Zheng, Y., Cao, Y., Chang, C.H.: UDhashing: physical unclonable function-based user-device hash for endpoint authentication. IEEE Trans. Industr. Electron. 66(12), 9559–9570 (2019)
Bian, W., Gope, P., Cheng, Y., Li, Q.: Bio-AKA: an efficient fingerprint based two factor user authentication and key agreement scheme. Future Gener. Comput. Syst. 109, 45–55 (2020)
Zhao, J., et al.: A Secure biometrics and PUFs-based authentication scheme with key agreement for multi-server environments. IEEE Access 8, 45292–45303 (2020)
Yang, W., Wang, S., Shahzad, M., Zhou, W.: A cancelable biometric authentication system based on feature-adaptive random projection. J. Inf. Secur. Appl. 58, 102704 (2021)
Arjona, R., Baturone, I.: A dual-factor access control system based on device and user intrinsic identifiers. In: IECON 2016–42nd Annual Conference of the IEEE Industrial Electronics Society, pp. 4731–4736. IEEE (2016)
Arjona, R., Prada-Delgado, M.A., Baturone, I., Ross, A.: Securing minutia cylinder codes for fingerprints through physically unclonable functions: an exploratory study. In: 2018 International Conference on Biometrics (ICB), pp. 54–60. IEEE (2018)
Liu, Y., Ling, J., Liu, Z., Shen, J., Gao, C.: Finger vein secure biometric template generation based on deep learning. Soft. Comput. 22(7), 2257–2265 (2017). https://doi.org/10.1007/s00500-017-2487-9
Yang, W., Wang, S., Hu, J., Zheng, G., Yang, J., Valli, C.: Securing deep learning based edge finger vein biometrics with binary decision diagram. IEEE Trans. Industr. Inf. 15(7), 4244–4253 (2019)
Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 1–27 (2011)
Rakshit, P., Basu, R., Paul, S., Bhattacharyya, S., Mistri, J., Nath, I.: Face Detection using Support Vector Mechine with PCA. Available at SSRN 3515989 (2020)
Saraswathi, M., Sivakumari, D.S.: Evaluation of PCA and LDA techniques for Face recognition using ORL face database. Int. J. Comput. Sci. Inf. Technol. 1, 810–813 (2015)
Danraka, S.S., Yahaya, S.M., Usman, A.D., Umar, A., Abubakar, A.M.: Discrete firefly algorithm based feature selection scheme for improved face recognition. Comput. Inf. Syst. 23(2), 23–34 (2019)
Gomez-Barrero, M., Galbally, J., Rathgeb, C., Busch, C.: General framework to evaluate unlinkability in biometric template protection systems. IEEE Trans. Inf. Forensics Secur. 13(6), 1406–1420 (2017)
Acknowledgement
This work was supported in part by the NSFC (Nos. 61976006, 61902003 and 61573023), NSF_AH (Nos. 1808085MF171 and 2108085MF206).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, H., Bian, W., Jie, B., Sun, S. (2022). A Novel Method of Template Protection and Two-Factor Authentication Protocol Based on Biometric and PUF. In: Meng, W., Conti, M. (eds) Cyberspace Safety and Security. CSS 2021. Lecture Notes in Computer Science(), vol 13172. Springer, Cham. https://doi.org/10.1007/978-3-030-94029-4_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-94029-4_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-94028-7
Online ISBN: 978-3-030-94029-4
eBook Packages: Computer ScienceComputer Science (R0)