RecUP-FL: Reconciling Utility and Privacy in Federated learning via User-configurable Privacy Defense

Author:

Cui Yue1ORCID,Meerza Syed Irfan Ali1ORCID,Li Zhuohang1ORCID,Liu Luyang2ORCID,Zhang Jiaxin3ORCID,Liu Jian1ORCID

Affiliation:

1. University of Tennessee, United States of America

2. Rutgers University, United States of America

3. Intuit AI Research, USA

Funder

NSF (National Science Foundation)

the Science Alliance?s StART program

Google Cloud

Publisher

ACM

Reference54 articles.

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2. 2018. California Consumer Privacy Act.https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5. 2018. California Consumer Privacy Act.https://leginfo.legislature.ca.gov/faces/codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5.

3. 2022. Apple A16 Bionic Chips Performance.https://www.cpu-monkey.com/en/cpu-apple_a16_bionic. 2022. Apple A16 Bionic Chips Performance.https://www.cpu-monkey.com/en/cpu-apple_a16_bionic.

4. 2022. Intel Core i7 12700H Core Performance.https://www.giznext.com/laptop-chipsets/intel-core-i7-12700h-chipset-gnt. 2022. Intel Core i7 12700H Core Performance.https://www.giznext.com/laptop-chipsets/intel-core-i7-12700h-chipset-gnt.

5. 2022. NVIDIA A100 GPU.https://www.nvidia.com/en-us/data-center/a100/. 2022. NVIDIA A100 GPU.https://www.nvidia.com/en-us/data-center/a100/.

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1. Game-theoretic analytics for privacy preservation in Internet of Things networks: A survey;Engineering Applications of Artificial Intelligence;2024-07

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