Achieving Privacy-Preserving and Verifiable Support Vector Machine Training in the Cloud-Reference-Cited by-同舟云学术

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

Author:

Hu Chenfei¹^ORCID,Zhang Chuan²^ORCID,Lei Dian³^ORCID,Wu Tong²^ORCID,Liu Ximeng⁴^ORCID,Zhu Liehuang²^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

2. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China

3. School of Information Science and Engineering, Lanzhou University, Lanzhou, China

4. School of Information Systems, Singapore Management University, Bras Basah, Singapore

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

China Postdoctoral Science Foundation

Shandong Provincial Key Research and Development Program

Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies

Beijing Institute of Technology (BIT) Research Fund Program for Young Scholars

BIT Research and Innovation Promoting Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

Reference47 articles.

2. A protocol for privacy preserving neural network learning on horizontal partitioned data;schlitter;Proc Privacy Stat Databases,2008

3. VCNN: Verifiable convolutional neural network based on zk-snarks;lee,2020

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