Work

Secure aggregation of sufficiently many private inputs

Year: 2025

Type: article

Abstract: Secure aggregation of distributed inputs is a well-studied problem. In this study, anonymity of inputs is achieved by assuring a minimal quota before publishing the outcome. We design and implement an efficient cryptographic protocol that mitigates the most important security risks and show its application in the cyber threat intelligence (CTI) domain. Our approach allows for generic aggregation and quota functions. With 20 inputs from different parties, we can do three secure and anonymous aggregations per second, and in a CTI community of 100 partners, 10, 000 aggregations could be performed during one night.

Source: Frontiers in Big Data

DOI: 10.3389/fdata.2025.1638307

Authors: Thijs Veugen, Gabriele Spini, Frank Muller

Institutions: Netherlands Organisation for Applied Scientific Research, University of Twente, AIT Austrian Institute of Technology GmbH

Language: English

Topic: Cryptography and Data Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,418

Funder: European Commission