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Title: RPM: Robust Anonymity at Scale

This work presents RPM, a scalable anonymous communication protocol suite using secure multiparty computation (MPC) with the offline-online model. We generate random, unknown permutation matrices in a secret-shared fashion and achieve improved (online) performance and the lightest communication and computation overhead for the clients compared to the state of art robust anonymous communication protocols. Using square-lattice shuffling, we make our protocol scale well as the number of clients increases. We provide three protocol variants, each targeting different input volumes and MPC frameworks/libraries. Besides, due to the modular design, our protocols can be easily generalized to support more MPC functionalities and security properties as they get developed. We also illustrate how to generalize our protocols to support two-way anonymous communication and secure sorting. We have implemented our protocols using the MP-SPDZ library suit and the benchmark illustrates that our protocols achieve unprecedented online phase performance with practical offline phases.

 
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Award ID(s):
1846316
NSF-PAR ID:
10497614
Author(s) / Creator(s):
;
Editor(s):
Mazurek, Michelle L; Sherr, Micah.
Publisher / Repository:
Creative Commons Attribution 4.0 license
Date Published:
Journal Name:
Proceedings on Privacy Enhancing Technologies
Volume:
2023
Issue:
2
ISSN:
2299-0984
Page Range / eLocation ID:
347 to 360
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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