Glass-Vault: A Generic Transparent Privacy-preserving Exposure Notification Analytics Platform
Lorenzo Martinico, Aydin Abadi, Thomas Zacharias, Thomas Win

TL;DR
Glass-Vault is a privacy-preserving platform enabling secure analysis of exposure notification data using a novel functional encryption variant, DD-Steel, ensuring transparency, security, and flexibility for COVID-19 contact tracing.
Contribution
It introduces Glass-Vault, a UC-secure protocol utilizing DD-Steel functional encryption for privacy-preserving data analysis in exposure notifications, addressing generality and transparency limitations.
Findings
First UC-secure protocol for privacy-preserving exposure data analysis.
Proposes DD-Steel, a dynamic, decentralized functional encryption variant.
Enables applications like infection heatmap generation.
Abstract
The highly transmissible COVID-19 disease is a serious threat to people's health and life. To automate tracing those who have been in close physical contact with newly infected people and/or to analyse tracing-related data, researchers have proposed various ad-hoc programs that require being executed on users' smartphones. Nevertheless, the existing solutions have two primary limitations: (1) lack of generality: for each type of analytic task, a certain kind of data needs to be sent to an analyst; (2) lack of transparency: parties who provide data to an analyst are not necessarily infected individuals; therefore, infected individuals' data can be shared with others (e.g., the analyst) without their fine-grained and direct consent. In this work, we present Glass-Vault, a protocol that addresses both limitations simultaneously. It allows an analyst to run authorised programs over the…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · COVID-19 Digital Contact Tracing · Vehicular Ad Hoc Networks (VANETs)
