Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions
Year: 2025
Type: article
Abstract: In a world where financial transactions are primarily performed or recorded online, protecting sensitive transaction details has become crucial. Roommates sharing housing costs or friends splitting travelling expenses may use applications such as Splitwise to easily track debts and minimize the number of individual repayments. However, these apps reveal potentially sensitive financial transaction activity to their operators. In this paper, we present Silent Splitter, a privacy-preserving payment splitting system which enables users to securely set up groups, perform transactions within those groups, and ``settle up'' without revealing group membership or any sensitive transaction details (such as the users involved or amount of money exchanged) to the system itself. Silent Splitter operates in the two server setting and uses Distributed Point Functions (DPFs) to securely record transactions. Of independent interest, we also present new protocols for proving knowledge of properties of DPFs as part of our system.
Authors: Margaret Pierce, Saba Eskandarian
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4412373425