A Secure Face Recognition for IoT-enabled Healthcare System

Alamgir Sardar, Saiyed Umer, Ranjeet Kr Rout, Shui Hua Wang, M. Tanveer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


In Healthcare, the Internet of Things (IoT)-enabled surveillance cameras capture thousands of images every day, where face recognition provides reliable security as well as smart treatment through patient sentiment analysis, emotion detection, automated nurse calls, and hospital traffic systems. In this article, a secure face recognition system for the IoT-enabled Healthcare system has been proposed. Here each registered person will be identified by his/her face biometric with strong template protection schemes. To protect the biometric information, three-step template protection techniques are proposed: (i) Cancelable biometrics, (ii) BioCrypto-Circuit, and (iii) BioCrypto-Protection. The performance of the proposed system has been tested on four benchmark face databases, CVL, IITK, Casia-Face-v5, and FERET. The results of the proposed system are reported in terms of the correct recognition rate and the equal error rate. These performances have also been compared with some state-of-the-art methods with respect to each employed database, which shows the novelty of the proposed system.

Original languageEnglish
Article number52
JournalACM Transactions on Sensor Networks
Issue number3
Publication statusPublished - 17 Apr 2023
Externally publishedYes


  • BioCryptosystem
  • Internet of Things
  • cancelable biometrics
  • face recognition
  • healthcare


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