Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions

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

Institutions

Publication Details

Journal
Proceedings on Privacy Enhancing Technologies
Published
2025-07-13
DOI
https://doi.org/10.56553/popets-2025-0168
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions

Saba Eskandarian, Margaret Pierce
Proceedings on Privacy Enhancing Technologies
Cryptography and Data Security
article

Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions

Saba Eskandarian, Margaret Pierce
article en

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.

Proceedings on Privacy Enhancing TechnologiesVol. 2025(4)
University of North Carolina at Chapel Hill (US)
Openalex Percentile: Top 92%
Cryptography and Data Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions — Saba Eskandarian, Margaret Pierce · Proceedings on Privacy Enhancing Technologies (2025) | TGRS Research Map | TGRS