Data Poisoning Attacks on Federated Machine Learning

Data Poisoning Attacks on Federated Machine Learning

Federated machine learning which enables resource-constrained node devices (e.g., Internet of Things (IoT) devices and smartphones) to establish a knowledge-shared model while keeping the raw data local, could provide privacy preservation, and economic benefit by designing an effective communication...

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Bibliographic Details
Main Authors: Cong, Y. (Author), Dong, J. (Author), Liu, J. (Author), Lyu, L. (Author), Sun, G. (Author), Wang, Q. (Author)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2022
Subjects:
Artificial intelligence
Bilevel optimization
Bi-level optimization
Communications protocols
data poisoning
Data poisoning
federated machine learning
Federated machine learning
Internet of things
Learning algorithms
Learning frameworks
Learning systems
Machine-learning
multitask learning
Multitask learning
Network protocols
Poisoning attacks
Resource constrained nodes
Target nodes
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