TY - GEN
T1 - A Strong Privacy-Preserving and Efficient Fingerprint Authentication via Clustering
AU - Liu, Jingwei
AU - Zhou, Zihan
AU - Sun, Rong
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - With the advancement of cloud technology, the storage and computing overhead in large-scale biometric authentication is mitigated by outsourcing data to the cloud. Since biometric features serve as a unique identifier bound to each individual, transmitting them directly to the cloud may bring about serious privacy disclosure risks. To guarantee users' biometric features, there are many solutions have been proposed. However, most of them neglect to protect identity security. In light of the challenges, this paper proposes a strong privacy-preserving fingerprint authentication via clustering. Besides safeguarding fingerprint features, the scheme also blurs the identities of users to enable anonymity of identity. Meanwhile, the authentication efficiency of the proposed scheme is improved by vector processing of fingerprints and fast retrieval of clustered identities. Furthermore, a dual-server matching architecture effectively reduces the communication overhead of the service provider. The security analysis and experimental results indicate that the proposed scheme provides strong privacy preservation while maintaining high efficiency.
AB - With the advancement of cloud technology, the storage and computing overhead in large-scale biometric authentication is mitigated by outsourcing data to the cloud. Since biometric features serve as a unique identifier bound to each individual, transmitting them directly to the cloud may bring about serious privacy disclosure risks. To guarantee users' biometric features, there are many solutions have been proposed. However, most of them neglect to protect identity security. In light of the challenges, this paper proposes a strong privacy-preserving fingerprint authentication via clustering. Besides safeguarding fingerprint features, the scheme also blurs the identities of users to enable anonymity of identity. Meanwhile, the authentication efficiency of the proposed scheme is improved by vector processing of fingerprints and fast retrieval of clustered identities. Furthermore, a dual-server matching architecture effectively reduces the communication overhead of the service provider. The security analysis and experimental results indicate that the proposed scheme provides strong privacy preservation while maintaining high efficiency.
KW - biometric authentication
KW - cloud computing
KW - homomorphic encryption
KW - Privacy preservation
UR - http://www.scopus.com/inward/record.url?scp=85187410424&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85187410424&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM54140.2023.10437834
DO - 10.1109/GLOBECOM54140.2023.10437834
M3 - Conference contribution
AN - SCOPUS:85187410424
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 5889
EP - 5894
BT - GLOBECOM 2023 - 2023 IEEE Global Communications Conference
T2 - 2023 IEEE Global Communications Conference, GLOBECOM 2023
Y2 - 4 December 2023 through 8 December 2023
ER -