A robust analysis of adversarial attacks on federated learning environments
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Adversarial attacks help adversaries evade FL system security detection and can generate poisoned samples to undermine the FL system accuracy.
“Adversarial attacks help adversaries evade FL system security detection and can generate poisoned samples to undermine the FL system accuracy (Goodfellow et al. 2014;Nair et al. 2023).”
From Survey: federated learning data security and privacy-preserving in edge-Internet of Things (2024) · cites this paper as Nair et al. 2023
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References 123 · Cited by 70
- Authors
- Nair, A. K., Raj, E. D., & Sahoo, J.
- Affiliations
- Indian Institute of Information Technology Kottayam (IN)
- Corresponding author
- Sahoo, Jayakrushna
- Venue
- Computer Standards & Interfaces
- Publisher
- Elsevier BV
- Published
- 2023-08
- Volume
- 86
- Pages
- 103723
- ISSN
- 0920-5489 (ISSN-L)
- OpenAlex
- W4313644996
- Cited by
- 70
- References
- 123
- Citations by year
- 2026: 13 · 2025: 24 · 2024: 25 · 2023: 8
- FWCI
- 6.20
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computer Standards & Interfaces (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Security and Verification in Computing
- Keywords
- federated learning security, adversarial attacks, data poisoning, inference attacks, backdoor attacks, data leakage, communication attacks, federated learning, attack taxonomy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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