A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

Muhammad Asad; Saima Shaukat; Ehsan Javanmardi; Jin Nakazato; Manabu Tsukada

doi:10.3390/app13106201

A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

Muhammad Asad, Saima Shaukat, Ehsan Javanmardi, Jin Nakazato, Manabu Tsukada

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	6201
Journal	Applied Sciences (Switzerland)
Volume	13
Issue number	10
DOIs	https://doi.org/10.3390/app13106201
Publication status	Published - May 2023
Externally published	Yes

ASJC Scopus Subject Areas

General Materials Science
Instrumentation
General Engineering
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes

Keywords

big data
data sharing
federated recommendation systems
privacy preserving

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10.3390/app13106201

Cite this

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title = "A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems",

keywords = "big data, data sharing, federated recommendation systems, privacy preserving",

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doi = "10.3390/app13106201",

language = "English",

volume = "13",

journal = "Applied Sciences (Switzerland)",

issn = "2076-3417",

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T1 - A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

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AU - Shaukat, Saima

AU - Javanmardi, Ehsan

AU - Nakazato, Jin

AU - Tsukada, Manabu

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KW - data sharing

KW - federated recommendation systems

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U2 - 10.3390/app13106201

DO - 10.3390/app13106201

M3 - Article

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JO - Applied Sciences (Switzerland)

JF - Applied Sciences (Switzerland)

IS - 10

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A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems

ASJC Scopus Subject Areas

Keywords

Access to Document

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