Fair detection of poisoning attacks in federated learning on non-i.i.d. data-Reference-Cited by-同舟云学术

Fair detection of poisoning attacks in federated learning on non-i.i.d. data

Published:2023-01-04 Issue:5 Volume:37 Page:1998-2023
ISSN:1384-5810
Container-title:Data Mining and Knowledge Discovery
language:en
Short-container-title:Data Min Knowl Disc

Author:

Singh Ashneet Khandpur,Blanco-Justicia Alberto,Domingo-Ferrer Josep^ORCID

Funder

horizon 2020 framework programme

icrea

Ministerio de Ciencia e Innovación

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s10618-022-00912-6.pdf

Reference34 articles.

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3. Blanco-Justicia A, Domingo-Ferrer J, Martínez S, Sánchez D, Flanagan A, Tan KE (2020) Achieving security and privacy in federated learning systems: survey, research challenges and future directions. arXiv preprint arXiv:2012.06810

4. Domingo-Ferrer J, Mateo-Sanz JM (2002) Practical data-oriented microaggregation for statistical disclosure control. IEEE Trans Knowl Data Eng 14(1):189–201

5. Domingo-Ferrer J, Torra V (2005) Ordinal, continuous and heterogeneous k-anonymity through microaggregation. Data Min Knowl Discov 11(2):195–212

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