Descrizione del progetto
Servizi Internet con protezione della privacy integrata
Ogni volta che si utilizza Internet, si affidano i propri dati a un unico fornitore di servizi. Ciò comporta un rischio, poiché la maggior parte dei fornitori di servizi si trova al di fuori dell’UE e si sono verificati molti incidenti in cui i governi, gli aggressori (esterni o interni) o errori umani hanno fatto trapelare i dati degli utenti. L’UE ha adottato misure per prevenire ulteriori attacchi di questo tipo, soprattutto imponendo l’applicazione del regolamento generale sulla protezione dei dati (GDPR), che obbliga le imprese a proteggere adeguatamente i dati dei loro utenti. Il progetto PSOTI, finanziato dall’UE, fornirà una protezione aggiuntiva applicando non solo misure legali, ma anche tecniche durante l’elaborazione dei dati sensibili dell’utente. Concretamente, verrà sviluppato un framework che consentirà agli utenti di scegliere tra più fornitori di servizi. I fornitori di servizi selezionati elaborano quindi congiuntamente i dati degli utenti in modo che rimangano protetti.
Obiettivo
Today, when using services on the Internet, users have to fully entrust a single service provider with their data. Many of these service providers are located outside the EU and there are cases where data has not only been leaked by attacks of outsiders or insiders, but also by governments who built backdoors into software or hardware, or forced service providers to give out sensitive user data. With the new EU General Data Protection Regulation (GDPR) also companies have an obligation to properly protect users’ data. My project PSOTI will eliminate the need to trust a single service provider and empower users to freely control their data. For this, the users can choose a subset of multiple service providers that they are willing to trust who jointly process their data and privacy is guaranteed even if all but one are compromised. The main goal of PSOTI is to develop privacy-preserving services for commonly used tasks on the Internet that are feature-rich and efficient enough for practical use. This will allow to privately store, retrieve, search, and process data, and help to comply with the GDPR and preserve the fundamental rights to privacy and the protection of personal data. As underlying technology, we will build a real-world secure multi-party computation (MPC) framework that can also be used for other large-scale privacy-preserving applications such as genomics or machine learning. To achieve our main goal, we will solve the following challenges: 1) Develop private query protocols on outsourced data that process complex queries such as Boolean formulas over string matches or range queries, and even hide the query’s structure. 2) Build a real-world MPC framework that scales to large functionalities, is highly parallelized, interoperable, and fully integrated. 3) Demonstrate real-world applicability for privacy-preserving and feature-rich services on the Internet such as file storage (going beyond Dropbox), surveys (going beyond Google Forms), and email.
Campo scientifico
- natural sciencesbiological sciencesgenetics
- natural sciencescomputer and information sciencessoftware
- natural sciencescomputer and information sciencesinternet
- natural sciencescomputer and information sciencescomputer securitydata protection
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-STG - Starting GrantIstituzione ospitante
64289 Darmstadt
Germania