Allowing privacy-preserving fog computing with digital identity assurance in remote clinical services

Nowadays, there is an increasing demand for cloud-based remote clinical services, both for diagnosis and monitoring. The COVID-19 pandemic has dramatically amplified this need. E-government programs should quickly go towards the expansion of this type of services, also to avoid that people (especially elderly) renounce treatment or adequate healthcare. However, to be effective, latency between IoT medical devices and the cloud should be reduced as much as possible. For this reason, fog computing appears the best approach, as part of the elaboration is moved closer to the user. However, some privacy threats arise. Indeed, these services can be delivered only based on secure digital identity and authentication systems, but the intermediate fog layer should learn nothing about the identity of users and the link among different service requests. In this paper, we propose a concrete solution to the above issue by leveraging eIDAS-compliant digital identity and by including a cryptographic protocol to provide anonymity and unlinkability of user's access to fog servers. Copyright © 2023 Inderscience Enterprises Ltd.

A Privacy-Preserving Solution for Proximity Tracing Avoiding Identifier Exchanging

Digital contact tracing is one of the actions useful, in combination with other measures, to manage an epidemic diffusion of an infectious disease in an after-lock-down phase. This is a very timely issue, due to the pandemic of COVID19 we are unfortunately living. Apps for contact tracing aim to detect proximity of users and to evaluate the related risk in terms of possible contagious. Existing approaches leverage BLE or GPS, or their combination, even though the prevailing approach is BLE-based and relies on a decentralized model requiring the mutual exchange of ephemeral identifiers among users' smartphones. Unfortunately, a number of security and privacy concerns exist in this kind of solutions, mainly due to the exchange of identifiers, while GPS-based solutions (inherently centralized) may suffer from threats concerning massive surveillance. In this paper, we propose a solution leveraging GPS to detect proximity, and BLE only to improve accuracy, with no exchange of identifiers. Unlike related existing solutions, no complex cryptographic mechanism is adopted, while ensuring that the server does not learn anything about locations of users. © 2020 IEEE.