Ruhr-Uni-Bochum
HGI

Copyright: HGI, stock.adobe.com: chinnarach

CASA Distinguished Lectures mit Carla Rafols Salvador (Pompeu Fabra University)

Das Thema ist "Scaling zkSNARKs".

Copyright: Department of Information and Communication Technologies, Universitat Pompeu Fabra; CASA

Wir laden herzlich zur nächsten CASA Distinguished Lecture mit Carla Rafols Salvador am Dienstag, 19. März 2024, ein.

Wann: 19.03.2024, 14:00 Uhr
Wo: Gebäude TZR ("MB"), Ebene 1, Raum S-MO-104, Universitätsstraße 142, 44799 Bochum
Online-Teilnahme: Zoom-Webinar

Abstract. Succinct Non-Interactive Arguments of Knowledge, or (zk)SNARKs, are commonly described as a key technology for improving privacy and scalability in blockchains. They are so useful because they allow both to hide or compress data while still proving statements about it: for example, they allow both to outsource transaction validation or keep transactions private. For many practical applications, one would like to prove statements about very large computations and prover complexity is currently the main efficiency barrier for achieving this. This talk will review some of the ongoing efforts and challenges for scaling zkSNARKs.

Bio. Carla Ràfols is a cryptographer based in Barcelona and a Tenure Track assistant professor at Pompeu Fabra University. Previously, she was a Marie Curie Fellow at the same university and a postdoctoral researcher at the Foundations of Cryptography Chair at Ruhr University Bochum. In the last few years, her research has focused on improving practical and theoretical aspects of zero-knowledge proofs. She is a co-author of more than 30 research papers in international journals and conferences. She regularly participates as a program committee member in the conferences of the International Association of Cryptologic Research. She has been a co-editor of a special issue, Mathematics of Zero-Knowledge, and a topical collection of the Journal of Cryptology, Modern Zero-Knowledge.

Allgemeiner Hinweis: Mit einer möglichen Nennung von geschlechtszuweisenden Attributen implizieren wir alle, die sich diesem Geschlecht zugehörig fühlen, unabhängig vom biologischen Geschlecht.