# An Intelligent Multimodal Biometric Authentication Model for Personalised Healthcare Services
## 1 Introduction  
In recent years, Personalised Healthcare (PH) has gone through promising advances with the potential to provide patient-tailored care by applying predictive analytics [1]. PH relies on data from patients' health records and measurements to predict unknown health issues that might arise in the near future. For example, PH could help patients forecast their weight gain in the coming two months, considering their daily diet and other lifestyle habits. Daily habits, diets and other lifestyle-related factors can cause someone to get diabetes or dementia earlier than expected. Early prediction of potential health issues can help proactively address them and provide adequate therapy before it worsens. Consequently, PH can help improve the quality of care and decrease related costs. A reliable PH system is comprised of several key components, as shown in Figure 1. In a PH system, various types of data about a patient are gathered through continuous monitoring of their health. The procedure includes utilising multiple devices, including the Internet of Things (IoT) sensors and smart devices. Patients discharged from hospitals, patients living remotely and the elderly living in residential care can take advantage ofsuch remote health monitoring. By remote monitoring of health status through IoT devices, the patients' personal health data can be stored in a highly-secured cloud-based data source. The monitoring data can then be used to perform intelligent analysis, often using cloud-based services, to predict potential health issues. In this model, the communication channel needs to be actively and continuously passing the data of the monitored patient to re-enforce the learning by the predictive analysis model. However, security and privacy concerns remain among the significant challenges in PH systems due to the reliance on IoT and cloud-based technologies [2]. In particular, the authentication challenges of these systems are unique because the IoT-based sensors and smart devices frequently produce a continuous stream of data and, thus, require continuous authentication to ensure that the data belongs to a particular patient. Specifically, the device's legitimacy needs to be continuously verified in a sensor-based PH network (a network of connected devices and IoT sensors that monitor a patient's health). Therefore, in such a context, it becomes challenging to verify that a set of sensors belong to the same PH network and they trust each other in providing and sharing patient data. Let us assume a PH network that belongs to a patient, [PERSON], and has sensors \(A\), \(B\), \(C\) and \(D\). [PERSON], on the other hand, has a PH network with three different sensors, \(X\), \(Y\) and \(Z\). Assume there is a rogue sensor \(W\) which tries to impersonate [PERSON] or [PERSON]'s network. In this case, the challenge is to employ a reliable method to verify that [PERSON]'s sensors should trust each other in sharing and communicating [PERSON]'s data, not [PERSON]'s and the rogue sensors. Such settings stimulate the need for a _continuous authentication_ method to verify that a set of sensors belongs to the same patient. Thus, it can trust that the data belongs to the same patient. Figure 2 depicts this scenario. Figure 1: PH Healthcare Architecture. Figure 2: Scenario: Single User Authentication. The second type of scenario that instigates such an authentication method involves a PH network that belongs to a group of users instead of a single user. They might be from the same household sharing the same network and sometimes the same devices. Figure 3 illustrates this scenario. Let us assume that [PERSON] and [PERSON] share the same PH network in this context. The sensors \(A\), \(B\), \(C\), \(D\) adjunct to [PERSON] and [PERSON]. The intruder, [PERSON], tries to intrude on the network using a rogue sensor \(W\). In this case, the network should employ a reliable method to continuously authenticate and verify [PERSON] and [PERSON]'s devices and reject [PERSON]'s rogue sensor.