Empirical study of privacy inference attack against deep reinforcement learning models

Most studies on privacy in machine learning have primarily focused on supervised learning, with little research on privacy concerns in reinforcement learning. However, our study has demonstrated that observation information can be extracted through trajectory analysis. In this paper, we propose a va...

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Bibliographic Details
Main Authors: Huaicheng Zhou, Kanghua Mo, Teng Huang, Yongjin Li
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Connection Science
Subjects:
Online Access:http://dx.doi.org/10.1080/09540091.2023.2211240
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