Paper 2018/1214

Instant Privacy-Preserving Biometric Authentication for Hamming Distance

Joohee Lee, Dongwoo Kim, Duhyeong Kim, Yongsoo Song, Junbum Shin, and Jung Hee Cheon


In recent years, there has been enormous research attention in privacy-preserving biometric authentication, which enables a user to verify him or herself to a server without disclosing raw biometric information. Since biometrics is irrevocable when exposed, it is very important to protect its privacy. In IEEE TIFS 2018, Zhou and Ren proposed a privacy-preserving user-centric biometric authentication scheme named PassBio, where the end-users encrypt their own templates, and the authentication server never sees the raw templates during the authentication phase. In their approach, it takes about 1 second to encrypt and compare 2000-bit templates based on Hamming distance on a laptop. However, this result is still far from practice because the size of templates used in commercialized products is much larger: according to NIST IREX IX report of 2018 which analyzed 46 iris recognition algorithms, size of their templates varies from 4,632-bit (579-byte) to 145,832-bit (18,229-byte). In this paper, we propose a new privacy-preserving user-centric biometric authentication (HDM-PPBA) based on Hamming distance, which shows a big improvement in efficiency to the previous works. It is based on our new single-key function-hiding inner product encryption, which encrypts and computes the Hamming distance of 145,832-bit binary in about 0.3 seconds on Intel Core i5 2.9GHz CPU. We show that it satisfies simulation-based security under the hardness assumption of Learning with Errors (LWE) problem. The storage requirements, bandwidth and time complexity of HDM-PPBA depend linearly on the bit-length of biometrics, and it is applicable to any large templates used in NIST IREX IX report with high efficiency.

Note: I fixed a typo in the author's name. (Jung Hee Cheon1 => Jung Hee Cheon)

Available format(s)
Publication info
Preprint. Minor revision.
Contact author(s)
skfro6360 @ snu ac kr
2018-12-24: revised
2018-12-23: received
See all versions
Short URL
Creative Commons Attribution


      author = {Joohee Lee and Dongwoo Kim and Duhyeong Kim and Yongsoo Song and Junbum Shin and Jung Hee Cheon},
      title = {Instant Privacy-Preserving Biometric Authentication for Hamming Distance},
      howpublished = {Cryptology ePrint Archive, Paper 2018/1214},
      year = {2018},
      note = {\url{}},
      url = {}
Note: In order to protect the privacy of readers, does not use cookies or embedded third party content.