A Secure Face Recognition for IoT-enabled Healthcare System

Abstract

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 paper, 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 steps template protection techniques have been proposed: (i) Cancelable biometrics , (ii) BioCrypto-Circuit , and (iii) BioCrypto-Protection schemes. 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.

A Review on Role of Image Processing Techniques to Enhancing Security of IoT Applications

“…Image processing is utilized to monitor and secure IoT-enabled areas. Image processing has improved security, therefore smart systems have integrated image processing-based and non-image processingbased security techniques [71], [72], [76], [77], [78], [79], [80]. 10.…”