Security Mechanisms of a Mobile Health Application for Promoting Physical Activity among Older Adults.

Physical activity contributes to the maintenance of health conditions and functioning. However, the percentage of older adults who comply with the recommendations for physical activity levels is low when compared to the same percentages on younger groups. The SmartWalk system aims to encourage older adults to perform physical activity (i.e., walking in the city), which is monitored and adjusted by healthcare providers for best results. The study reported in this article focused on the implementation of SmartWalk security services to keep personal data safe during communications and while at rest, which were validated considering a comprehensive use case. The security framework offers various mechanisms, including an authentication system that was designed to complement the pairs of usernames and passwords with trusted execution environments and token-based features, authorization with different access levels, symmetric and asymmetric key cryptography, critical transactions review, and logging supported by blockchain technology. The resulting implementation contributes for a common understanding of the security features of trustful smart cities' applications, which conforms with existing legislation and regulations.

Building an IoT Platform Based on Service Containerisation.

IoT platforms have become quite complex from a technical viewpoint, becoming the cornerstone for information sharing, storing, and indexing given the unprecedented scale of smart services being available by massive deployments of a large set of data-enabled devices. These platforms rely on structured formats that exploit standard technologies to deal with the gathered data, thus creating the need for carefully designed customised systems that can handle thousands of heterogeneous data sensors/actuators, multiple processing frameworks, and storage solutions. We present the SCoT2.0 platform, a generic-purpose IoT Platform that can acquire, process, and visualise data using methods adequate for both real-time processing and long-term Machine Learning (ML)-based analysis. Our goal is to develop a large-scale system that can be applied to multiple real-world scenarios and is potentially deployable on private clouds for multiple verticals. Our approach relies on extensive service containerisation, and we present the different design choices, technical challenges, and solutions found while building our own IoT platform. We validate this platform supporting two very distinct IoT projects (750 physical devices), and we analyse scaling issues within the platform components.

A Parser to Support the Definition of Access Control Policies and Rules Using Natural Languages.

As a consequence of the epidemiological transition towards non-communicable diseases, integrated care approaches are required, not solely focused on medical purposes, but also on a range of essential activities for the maintenance of the individuals' quality of life. In order to allow the exchange of information, these integrated approaches might be supported by digital platforms, which need to provide trustful environments and to guarantee the integrity of the information exchanged. Therefore, together with mechanisms such as authentication, logging or auditing, the definition of access control policies assumes a paramount importance. This article focuses on the development of a parser as a component of a platform to support the care of community-dwelling older adults, the SOCIAL platform, to allow the definition of access control policies and rules using natural languages.

Preserving Privacy when Querying OMOP CDM Databases.

Anonymisation is currently one of the biggest challenges when sharing sensitive personal information. Its importance depends largely on the application domain, but when dealing with health information, this becomes a more serious issue. A simpler approach to avoid inadequate disclosure is to ensure that all data that can be associated directly with an individual is removed from the original dataset. However, some studies have shown that simple anonymisation procedures can sometimes be reverted using specific patients' characteristics. In this work, we propose a secure architecture to share information from distributed databases without compromising the subjects' privacy. The anonymiser system was validated using the OMOP CDM data schema, which is widely adopted in observational research studies.