Abstract
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 personalized healthcare systems.
Highlights
The Internet of Things (IoT) and Cloud Computing technologies are shaping and modernising healthcare services
TN stands for True Negative, TP stands for True Positive, FN stands for False Negative and FP
Based on the reported outcomes of the two phases of the experiment conducted in this work, it is evident that a fused signal of ECG and PPG can be used to authenticate users based on their biometric traits without compromising the accuracy of the model
Summary
The Internet of Things (IoT) and Cloud Computing technologies are shaping and modernising healthcare services. Healthcare providers across Europe and Asia are working on projects to integrate the IoT and Cloud Computing technologies in their health services [5,6,7]. Most of these works are intended for hospital-based care. Healthcare workers, thirds parties and other applications could access the patients’ records and provide personalized health plans In such a complex, dynamic and ever-expanding environment, obtaining the user’s consent and administering authorization and identity management models are challenging to meet. The framework incorporates a new biometric-based authentication method This method uses a fusion of PPG and ECG signals to uniquely identify users. It is noted that the model successfully identified all 25 users used in the experiment
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