Open Access

Linear-Complexity Private Function Evaluation is Practical - Performance measurement data

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README.md (3.01 KB)
 eval_perf_UC.py (6.26 KB)
 eval_perf_MPC.py (3.25 KB)
 eval_perf_KM11.py (6.42 KB)
 mem_UC_WAN.csv (210 B)

Date

2020-09-14

Type

Dataset

Authors

Holz, Marco
Kiss, Ágnes
Rathee, Deevashwer
Schneider, ThomasORCID 0000-0001-8090-1316

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

Performance measurement data for the paper 'Linear-Complexity Private Function Evaluation is Practical'

Keywords

cryptographic protocols, private function evaluation, homomorphic encryption, secure computation

Citation

Identifier

https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2487
 https://doi.org/10.25534/tudatalib-321

Endorsement

Related Resources

Is Supplement To
https://ia.cr/2020/853
Is Derived From
https://github.com/encryptogroup/linearPFE

DFG Classification

4.43-03 Sicherheit und Verlässlichkeit, Betriebs-, Kommunikations- und verteilte Systeme

Project(s)

Faculty

Collections

Linear-Complexity Private Function Evaluation is Practical

License

CC BY 4.0 - Attribution 4.0 International
Except where otherwise noted, this license is described as CC BY 4.0 - Attribution 4.0 International