Related papers: Watermarking Decision Tree Ensembles

Watermarking Decision Tree Ensembles

URL: http://arxiv.org/abs/2410.04570v1
Date: Sun, 6 Oct 2024 17:56:13 GMT
Title: Watermarking Decision Tree Ensembles
Authors: Stefano Calzavara, Lorenzo Cazzaro, Donald Gera, Salvatore Orlando,
Abstract summary: We present the first watermarking scheme for decision tree ensembles, focusing in particular on random forest models. We show excellent results in terms of accuracy and security against the most relevant threats.
Score: 3.5621555706183896
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Protecting the intellectual property of machine learning models is a hot topic and many watermarking schemes for deep neural networks have been proposed in the literature. Unfortunately, prior work largely neglected the investigation of watermarking techniques for other types of models, including decision tree ensembles, which are a state-of-the-art model for classification tasks on non-perceptual data. In this paper, we present the first watermarking scheme designed for decision tree ensembles, focusing in particular on random forest models. We discuss watermark creation and verification, presenting a thorough security analysis with respect to possible attacks. We finally perform an experimental evaluation of the proposed scheme, showing excellent results in terms of accuracy and security against the most relevant threats.

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