Two-Party Multi-Point Function Secret Sharing
Name
Erki Külaots
Abstract
Multiparty computation (MPC) is an important field of cryptography that deals with protecting the privacy of data, while allowing to do computation on that data. A key part of MPC is the parties involved having correlated randomness that they can use to make the computation or the communication between themselves more efficient, while still preserving the privacy of the data. Examples of these correlations include random oblivious transfer (OT) correlations, oblivious linear-function evaluation (OLE) correlations, multiplication triples (also known as Beaver triples) and one-time truth tables. Multi-point function secret sharing (FSS) has been shown to be a great building block for (pseudo-)random correlation generation. The main question is how to construct fast and efficient multi-point FSS schemes. Here we propose a novel approach to multi-point FSS using tree structure, pseudorandom generator and systems of linear equations. Our scheme MultiFunUSLESS has similar efficiency parameters to previously proposed multi-point FSS schemes and is more efficient in the evaluation phase, this means it is the best option in some use cases. On the whole, it provides us with a new perspective, how to construct multi-point FSS schemes. In all walks of computer science efficiency is key: algorithms should be faster, take less resources and communication should be minimal and that is what we are trying to achieve with our work.
Graduation Thesis language
English
Graduation Thesis type
Master - Computer Science
Supervisor(s)
Toomas Krips
Defence year
2024