###### Abstract  
Globally, 77% of the elderly aged 65 and above suffer from multiple chronic ailments, according to recent research. However, several barriers within the healthcare system in the developing world hinder the adoption of home-based patient management, hence the need for the IoMT, whose application raises security concerns, particularly in authentication. Several authentication techniques have been proposed; however, they lack a balance of security and usability. This paper proposes a Naive Bayes based adaptive user authentication app that calculates the risk associated with a login attempt on an Android device for elderly users, using their health conditions, risk score, and available authenticators. This authentication technique guided by the MAPE-K\({}_{\text{HMT}}\) framework makes use of embedded smartphone sensors. Results indicate a 100% and 98.6% accuracy in usable-security metrics, while cross-validation and normalization results also support the accuracy, efficiency, effectiveness, and usability of our model with room for scaling it up without computational costs and generalizing it beyond SSA. The post-deployment evaluation also confirms that users found the app usable and secure. A few areas need further refinement to improve the accuracy, usability, security, and acceptance but the model shows potential to improve users' compliance with IoMT security, thereby promoting the attainment of SDG3. elderly patients; SSA; chronic ailments; risk calculation; adaptive authentication; smartphone; usable security +
Footnote †: journal: Cybersecurity and Privacy  
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affordability and sensor availability, enabling non-invasive vital parameters monitoring, communication, and healthy behavior encouragement. However, the implementation of the IoMT faces challenges concerning the privacy and security of patient data [9, 11, 12]. Generally, Internet of Things (IoT) systems cater to both technical and non-technical users [13], but most end users, including elderly individuals, lack technological proficiency and are unlikely to implement security measures, making them susceptible to potential attacks [14]. At the same time, the development of security protocols often fails to account for the health issues prevalent in older populations [15, 16], but when it comes to authentication, elderly users have their authenticator preferences [17]. Although smartphones are commonly utilized for authentication purposes, there is little empirical support regarding their effectiveness across various age demographics, including the elderly [5]. Despite ongoing research on suitable authentication techniques [1], there is a lack of extensive research on the practicality of authentication technologies for senior citizens and individuals with disabilities [18]. Most previous research has either focused on device authentication [19], security without usability and vice versa [20, 21, 22], physiological authentication [23], health monitoring and well-being only, and does not consider user age. As a result, there is essentially a dearth of research on IoMT user authentication that takes into account senior users' capabilities. Since smartphones are widely used devices that people of all ages can use for communication and other purposes, they make good candidates for use in IoMT authentication. Therefore, research on smartphone-based user authentication mechanisms for the elderly is crucial. This research aimed to improve usable security by developing and implementing an Android-based adaptive authentication system for elderly IoMT users. The primary objectives were as follows:  
1. Develop a Naive Bayes Android-based adaptive authentication model for IoMT hardware and software that considers elderly users' medical conditions and risk scores for suitable authenticators;
2. Assess the effectiveness of the proposed model in authenticating elderly users.