TrapMI: A Data Protection Method to Resist Model Inversion Attacks in Split Learning

Split learning is a neural network training approach that can overcome the limitations of traditional deep neural networks in edge artificial intelligence environments. It offers the advantage of privacy protection because it transmits intermediate features that are calculated via the client-side mo...

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Bibliographic Details
Main Authors: Hyunsik Na, Daeseon Choi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10902388/
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