Privacy-Preserving Deep Learning Based on Multiparty Secure Computation: A Survey

Deep learning (DL) has demonstrated superior success in various of applications, such as image classification, speech recognition, and anomalous detection. The unprecedented performance gain of DL largely depends on tremendous training data, high-performance computation resources, and well-designed...

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Veröffentlicht in:	IEEE internet of things journal Jg. 8; H. 13; S. 10412 - 10429
Hauptverfasser:	Zhang, Qiao, Xin, Chunsheng, Wu, Hongyi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Cloud computing Computational modeling Data encryption Data models Data privacy Deep learning Deep learning (DL) Image classification linear and nonlinear computations Machine learning Mathematical models Object recognition Outsourcing Parameters Predictive models Privacy privacy preserving Servers Speech recognition State-of-the-art reviews Training
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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