Secure training of decision trees with continuous attributes

Secure training of decision trees with continuous attributes

We apply multiparty computation (MPC) techniques to show, given a database that is secret-shared among multiple mutually distrustful parties, how the parties may obliviously construct a decision tree based on the secret data. We consider data with continuous attributes (i.e., coming from a large dom...

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Bibliographic Details
Main Authors: Abspoel Mark, Escudero Daniel, Volgushev Nikolaj
Format: Article
Language:English
Published: Sciendo 2021-01-01
Series:Proceedings on Privacy Enhancing Technologies
Subjects:
decision trees
multiparty computation
privacy-preserving machine learning
Online Access:https://doi.org/10.2478/popets-2021-0010

Internet

https://doi.org/10.2478/popets-2021-0010

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