A Federal-Based Canonical Correlation Analysis Approach for Privacy Preserving in Crowdsensing

LI Wenping, ZHU Helei

Journal of Systems Science and Mathematical Sciences ›› 2022, Vol. 42 ›› Issue (11) : 2859-2873.

PDF(7259 KB)
中国科学院数学与系统科学研究院期刊网
PDF(7259 KB)
Journal of Systems Science and Mathematical Sciences ›› 2022, Vol. 42 ›› Issue (11) : 2859-2873. DOI: 10.12341/jssms22106

A Federal-Based Canonical Correlation Analysis Approach for Privacy Preserving in Crowdsensing

  • LI Wenping, ZHU Helei
Author information +
History +

HeighLight

{{article.keyPoints_en}}

Abstract

{{article.zhaiyao_en}}

Key words

QR code of this article

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations
{{article.zuoZheEn_L}}. {{article.title_en}}. Journal of Systems Science and Mathematical Sciences, 2022, 42(11): 2859-2873 https://doi.org/10.12341/jssms22106

References

Publishing order | Descend order by publishing year | Descend order by cited within

References

{{article.reference}}

Funding

RIGHTS & PERMISSIONS

{{article.copyrightStatement_en}}
{{article.copyrightLicense_en}}
PDF(7259 KB)

Accesses

Citation

Detail
Sections
Recommended

/

〈 〉