Privacy-Preserving Authentication Scheme for 5G Cloud-Fog Hybrid with Soft Biometrics

Jiahui Wang, Yulong Fu, Mengru Liu, Jin Cao, Hui Li, Zheng Yan

Abstract: The feature of Enhanced Mobile Broadband (eMBB) and Cloud-Fog hybrid architecture in 5G significantly enhance the communication and computation capabilities of 5G devices, and make the biometric traits collection, recognition and authentication become possible. However, since biometrics such as face ID, fingerprint, etc. are belonging to user’s privacy, by considering the curiosity of cloud server and the law of General Data Protection Regulation (GDPR), we can’t use biometrics directly in 5G cloud-fog hybrid scenarios. To solve this problem, in this paper, we propose a privacy-preserving authentication scheme based on soft biometric traits (PPA-SBT). In our scheme, soft biometrics without privacy attributes are designed to protect the biometrics with privacy attributes through encryption, and improve the recognition speed and accuracy rate. We conducted the theoretical security analysis of the proposed scheme with formal method and also conducted experiments with real dataset and public datasets respectively, the experimental results demonstrate the feasibility and convenience of PPA-SBT.

External IDs:dblp:conf/ispec/WangFLCLY23