The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/56552cc8-7ebf-46ce-a6e0-668dd6065eb2

Palazzo, Marco; Dekker, Florine (2025): Source code underlying the publication: Privacy-Preserving Data Aggregation with Public Verifiability Against Internal Adversaries. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/56552cc8-7ebf-46ce-a6e0-668dd6065eb2.v1

Categories

• Other Information and Computing Sciences
• Information and Computing Sciences

Keywords

multi-party computation privacy-preserving summation public verifiability secure multi-party computation secure summation

Licence

CC BY-SA 4.0

Interoperability

• RO-Crate Metadata

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by Marco Palazzo , Florine Dekker

Python code to reproduce results presented in the paper "Privacy-Preserving Data Aggregation with Public Verifiability Against Internal Adversaries". Specifically, to run an implementation of the mPVAS family of protocols and measures its runtime.

The source code was published by the paper's authors some time after the paper was published.

Usage

Minimal usage instructions: On a system running Debian 12, with GNU Make installed, run make install test run plot.

See README.md inside the git repository for detailed usage instructions.

Code

The source code is available as a git repository. The relevant code is stored in the src directory.

History

• 2025-06-11 first online, published, posted

Publisher

4TU.ResearchData

Format

Python code

References

• https://www.usenix.org/conference/usenixsecurity24/presentation/palazzo

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems