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DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks
[article]
2018
arXiv
pre-print
This paper proposes DeepMarks, a novel end-to-end framework for systematic fingerprinting in the context of Deep Learning (DL). Remarkable progress has been made in the area of deep learning. Sharing the trained DL models has become a trend that is ubiquitous in various fields ranging from biomedical diagnosis to stock prediction. As the availability and popularity of pre-trained models are increasing, it is critical to protect the Intellectual Property (IP) of the model owner. DeepMarks
arXiv:1804.03648v1
fatcat:iday65xthjdpzcg52h3zzpy67u