In each winter term BiCDaS offers a lecture series on data science. It takes place on six different Fridays throughout the term.
We are proud to once again have convinced a highly skilled set of internal and external data science professionals to join us as speakers.
This lecture will be held by Dr Hendrik Ballhausen (SMPC, Ludwig-Maximilians-Universität München)
The free flow of information is the life blood of digital industries and much of modern science. Yet collaboration is impeded by inefficiently low data sharing as proprietary data is kept in private siloes. Often, data exchange is prevented by competition and lack of trust between data owners, consumer and privacy concerns, and data protection regulation. Is there a way to reconcile digital collaboration with data privacy?
Secure Multiparty Computation (SMPC), a disruptive technology, promises to do just that. It simulates a virtual trusted third party as a cryptographic network between the parties. The network only exists as long as all parties actively engage in the the calculation, and the joint result is distributed to all. The individual private data, however, remains with the original data owners, and nothing can be learned by an external or internal attacker except for the intended result of the computation.
In many ways, secure multiparty computation is similar to the blockchain. Both work in trustless settings without a central authority. However, while distributed ledger technologies provide trust, reliability, and transparency; secure multiparty computation provides privacy, security, dynamic consent, and control over proprietary data.
This talk provides a brief non-technical introduction to secure multiparty computation. A proof-of-principle is presented in which proprietary patient data was jointly evaluated between two remote university hospitals.