A Smart Biometric Identity Management Framework for Personalised IoT and Cloud Computing-Based Healthcare Services

Sensors

Farnaz Farid¹  Farhad Ahamed²  Mahmoud Elkhodr³  Fariza Sabrina³  Ergun Gide³ 

[1] School of Computer Science, The University of Sydney, Darlington, NSW 2008, Australia;School of Computer, Data and Mathematical Sciences, Western Sydney University, Kingswood, NSW 2747, Australia;School of Engineering and Technology, Central Queensland University, Sydney, NSW 2000, Australia;

关键词: identity management;    personalised healthcare;    authentication;    cloud computing;    internet of things;    fused-based biometric;   

DOI  :  10.3390/s21020552

来源: DOAJ

【 摘 要 】

This paper proposes a novel identity management framework for Internet of Things (IoT) and cloud computing-based personalized healthcare systems. The proposed framework uses multimodal encrypted biometric traits to perform authentication. It employs a combination of centralized and federated identity access techniques along with biometric based continuous authentication. The framework uses a fusion of electrocardiogram (ECG) and photoplethysmogram (PPG) signals when performing authentication. In addition to relying on the unique identification characteristics of the users’ biometric traits, the security of the framework is empowered by the use of Homomorphic Encryption (HE). The use of HE allows patients’ data to stay encrypted when being processed or analyzed in the cloud. Thus, providing not only a fast and reliable authentication mechanism, but also closing the door to many traditional security attacks. The framework’s performance was evaluated and validated using a machine learning (ML) model that tested the framework using a dataset of 25 users in seating positions. Compared to using just ECG or PPG signals, the results of using the proposed fused-based biometric framework showed that it was successful in identifying and authenticating all 25 users with 100% accuracy. Hence, offering some significant improvements to the overall security and privacy of personalised healthcare systems.

【 授权许可】

Unknown