Achieving Privacy-Preserving and Verifiable Support Vector Machine Training in the Cloud

With the proliferation of machine learning, the cloud server has been employed to collect massive data and train machine learning models. Several privacy-preserving machine learning schemes have been suggested recently to guarantee data and model privacy in the cloud. However, these schemes either m...

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Veröffentlicht in:	IEEE transactions on information forensics and security Jg. 18; S. 1
Hauptverfasser:	Hu, Chenfei, Zhang, Chuan, Lei, Dian, Wu, Tong, Liu, Ximeng, Zhu, Liehuang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Cloud computing Computational modeling Cryptography Data models data perturbation homomorphic encryption Machine learning Perturbation Privacy Privacy-preserving Servers support vector machine Support vector machines Training Verification verification mechanism
ISSN:	1556-6013, 1556-6021
Online-Zugang:	Volltext
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