Types of Attacks against Federated Neural Networks and Protection Methods

Federated learning is a technology for privacy preserving learning in distributed storage systems. This kind of learning allows one to create a general predictive model while storing all the data in their own’ storage systems. Several devices take part in training the general model, and each device...

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Veröffentlicht in:	Programming and computer software Jg. 51; H. 6; S. 409 - 414
Hauptverfasser:	Kostenko, V. A., Selezneva, A. E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Moscow Pleiades Publishing 01.12.2025 Springer Nature B.V
Schlagworte:	Artificial Intelligence Classification Computer Science Data exchange Data transfer (computers) Devices Federated learning Keyboards Machine learning Methods Neural networks Operating Systems Poisons Prediction models Privacy Software Engineering Software Engineering/Programming and Operating Systems Storage systems evasion attacks neural networks data recovery attacks neural network protection logical inference attacks poisoning attacks federated classifiers attacks against neural networks security of neural networks
ISSN:	0361-7688, 1608-3261
Online-Zugang:	Volltext
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