Project description
Internet services with built-in privacy protection
Whenever someone is using the Internet, they must entrust their data to a single service provider. This poses a risk, as many service providers are located outside the EU and there have been a lot of incidents where either governments, attackers (external or internal), or human errors leaked user data. The EU has taken measures to prevent further attacks of this kind, mainly by enforcing the General Data Protection Regulation (GDPR), which obligates companies to properly protect their users' data. The EU-funded project PSOTI will provide additional protection by applying not only legal, but also technical measures when processing sensitive user data. Concretely, a framework will be developed that allows users to choose among multiple service providers. The selected service providers then jointly process the users’ data so that it remains protected.
Objective
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.
Fields of science
- 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
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting GrantHost institution
64289 Darmstadt
Germany