Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation

Du Nguyen Duy, Michael Affenzeller, Ramin Nikzad-Langerodi

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

Symbolic Regression is a powerful data-driven technique that searches for mathematical expressions that explain the relationship between input variables and a target of interest. Due to its efficiency and flexibility, Genetic Programming can be seen as the standard search technique for Symbolic Regression. However, the conventional Genetic Programming algorithm requires storing all data in a central location, which is not always feasible due to growing concerns about data privacy and security. While privacy-preserving research has advanced recently and might offer a solution to this problem, their application to Symbolic Regression remains largely unexplored. Furthermore, the existing work only focuses on the horizontally partitioned setting, whereas the vertically partitioned setting, another popular scenario, has yet to be investigated. Herein, we propose an approach that employs a privacy-preserving technique called Secure Multiparty Computation to enable parties to jointly build Symbolic Regression models in the vertical scenario without revealing private data. Preliminary experimental results indicate that our proposed method delivers comparable performance to the centralized solution while safeguarding data privacy.

OriginalspracheEnglisch
TitelGECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten2420-2428
Seitenumfang9
ISBN (elektronisch)9798400701207
DOIs
PublikationsstatusVeröffentlicht - 15 Juli 2023
Veranstaltung2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion - Lisbon, Portugal
Dauer: 15 Juli 202319 Juli 2023

Publikationsreihe

NameGECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion

Konferenz

Konferenz2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion
Land/GebietPortugal
OrtLisbon
Zeitraum15.07.202319.07.2023

Fingerprint

Untersuchen Sie die Forschungsthemen von „Towards Vertical Privacy-Preserving Symbolic Regression via Secure Multiparty Computation“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren