Deep index-of-maximum hashing for face template protection

Jiandong Cui, Andrew Beng Jin Teoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face authentication is one of the most common biometrics available nowadays. Ensuring security of facial templates is vital to circumvent impersonation and privacy invasion. One of the notable remedies for facial template protection is cancelable biometrics whereby the compromised template can be revoked and replaced. In this work, we propose a cancelable facial template technique based on the Index-of- Maximum (IoM) hashing by means of deep neural networks, termed as Deep IoM (DIoM) hashing. Unlike data-agnostic IoM hashing, the DIoM hashing is data-driven and trained by supervision to render a discriminative cancelable facial template. The DIoM hashing relies upon a permutable pretrained deep feature learning network and a hashing network responsible for optimizing the DIoM hash codes. The hashing network consolidates maxout and softmax function, namely softmaxout to approximate the discrete DIoM hash code. A dedicated loss function is designed in order to achieve similaritypreserving learning, code balancing and quantization. The proposed network is assessed on unconstraint Labeled Faces in the Wild dataset and shown outperformed vanilla IoM hashing significantly.

Original languageEnglish
Title of host publication2020 5th International Conference on Computer and Communication Systems, ICCCS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages413-418
Number of pages6
ISBN (Electronic)9781728161365
DOIs
Publication statusPublished - 2020 May
Event5th International Conference on Computer and Communication Systems, ICCCS 2020 - Shanghai, China
Duration: 2020 May 152020 May 18

Publication series

Name2020 5th International Conference on Computer and Communication Systems, ICCCS 2020

Conference

Conference5th International Conference on Computer and Communication Systems, ICCCS 2020
CountryChina
CityShanghai
Period20/5/1520/5/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computational Mathematics
  • Control and Optimization
  • Hardware and Architecture

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  • Cite this

    Cui, J., & Teoh, A. B. J. (2020). Deep index-of-maximum hashing for face template protection. In 2020 5th International Conference on Computer and Communication Systems, ICCCS 2020 (pp. 413-418). [9118594] (2020 5th International Conference on Computer and Communication Systems, ICCCS 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCS49078.2020.9118594