Non so se questo approccio è passato in lista. Nel white paper è interessante la discussione tra un approccio centralizzato e uno decentrato. <https://github.com/DP-3T/documents> Decentralized Privacy-Preserving Proximity Tracing This repository contains a proposal for a secure and privacy-preserving decentralized privacy-preserving proximity tracing system. Its goal is to simplify and accelerate the process of identifying people who have been in contact with an infected person, thus providing a technological foundation to help slow the spread of the SARS-CoV-2 virus. The system aims to minimise privacy and security risks for individuals and communities and guarantee the highest level of data protection. By publishing this document we seek feedback from a broad audience on the high-level design, its security and privacy properties, and the functionality it offers; so that further protection mechanisms can be added if weaknesses are identified. The white paper document is accompanied by an overview of the data protection aspects of the design, and a three page simplified introduction to the protocol. If you have a similar project and you believe it would be beneficial to collaborate or exchange ideas drop an email here: dp3t@groupes.epfl.ch. The following people are behind this design: EPFL: Prof. Carmela Troncoso, Prof. Mathias Payer, Prof. Jean-Pierre Hubaux, Prof. Marcel Salathé, Prof. James Larus, Prof. Edouard Bugnion, Dr. Wouter Lueks, Theresa Stadler, Dr. Apostolos Pyrgelis, Dr. Daniele Antonioli, Ludovic Barman, Sylvain Chatel ETHZ: Prof. Kenneth Paterson, Prof. Srdjan Capkun, Prof. David Basin, Dennis Jackson KU Leuven: Prof. Bart Preneel, Prof. Nigel Smart, Dr. Dave Singelee, Dr. Aysajan Abidin TU Delft: Prof. Seda Gürses University College London: Dr. Michael Veale CISPA: Prof. Cas Cremers University of Oxford: Dr. Reuben Binns TU Berlin / Fraunhofer HHI: Prof. Thomas Wiegand Anche: <https://blog.symbolic.software/2020/04/05/dp-3t-verifpal/>