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Cicala, F., Wang, W., Wang, T., Li, N., Bertino, E., Liang, F. and Yang, Y. (2021) PURE: A Framework for Analyzing Proximity-Based Contact Tracing Protocols. ACM Computing Surveys, 55, Article No. 3.
https://doi.org/10.1145/3485131

has been cited by the following article:

• TITLE: Privacy Protection in COVID Data Tracking: Textual Analysis of the Literature

  AUTHORS: Antonella Massari, Viviana D’Addosio, Vittoria Claudia De Nicolò, Samuela L’Abbate

  KEYWORDS: Tracking, Privacy, Blockchain, Textual Analysis

  JOURNAL NAME: Applied Mathematics, Vol.15 No.3, March 29, 2024

  ABSTRACT: The literary review presented in the following paper aims to analyze the tracking tools used in different countries during the period of the COVID-19 pandemic. Tracking apps that have been adopted in many countries to collect data in a homogeneous and immediate way have made up for the difficulty of collecting data and standardizing evaluation criteria. However, the regulation on the protection of personal data in the health sector and the adoption of the new General Data Protection Regulation in European countries has placed a strong limitation on their use. This has not been the case in non-European countries, where monitoring methodologies have become widespread. The textual analysis presented is based on co-occurrence and multiple correspondence analysis to show the contact tracing methods adopted in different countries in the pandemic period by relating them to the issue of privacy. It also analyzed the possibility of applying Blockchain technology in applications for tracking contagions from COVID-19 and managing health data to provide a high level of security and transparency, including through anonymization, thus increasing user trust in using the apps.