Irene is an Italian cryptographer based in Switzerland. She completed her Ph.D. at Aarhus University (Denmark) in 2016 after her undergraduate studies in Mathematics at Pisa University (Italy). After completing her Ph.D., she was a research assistant (postdoc), first in the USA (Madison, WI) and then in Italy (ISI Foundation, Turin). Her postdoctoral work focused on privacy-preserving machine-learning. Her research interests lie in the area of cryptographic protocol design and in the intersections between cryptography and other fields such machine-learning and blockchain technology.
In Part One, we traced the intellectual and technological history of modern implementations of distributed ledger technology. Now let’s take a stroll through the technological landscape around the time of Filecoin’s release:
The Filecoin network is launching in the middle of a revolution in internet architecture, where vulnerable centralized services dependent on trusted parties are being replaced with resilient decentralized solutions based on verifiable computation, and internet services are being relocated from inefficient central monoliths to the far reaches of the network by peer-to-peer markets.
In this paper we present a new 2-party protocol for secure computation over rings of the form Z2k. As many recent efficient MPC protocols supporting dishonest majority, our protocol consists of a heavier (input-independent) pre-processing phase and a very efficient online stage.
Machine learning is being increasingly used by individuals, research institutions, and corporations. This has resulted in the surge of Machine Learning-as-a-Service (MLaaS) - cloud services that provide (a) tools and resources to learn the model, and (b) a user-friendly query interface to access the model.