Double layer federated security learning architecture for artificial intelligence of things
Federated learning, as a distributed machine learning architecture, can complete model co-training while protecting data privacy, and is widely used in Artificial Intelligence of Things. However, there are often security threats such as privacy breaches and poisoning attacks in federated learning. I...
Saved in:
Main Authors: | ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin |
---|---|
Format: | Article |
Language: | English |
Published: |
POSTS&TELECOM PRESS Co., LTD
2024-12-01
|
Series: | 网络与信息安全学报 |
Subjects: | |
Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024081 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Federated Reinforcement Learning in Stock Trading Execution: The FPPO Algorithm for Information Security
by: Haogang Feng, et al.
Published: (2025-01-01) -
Intelligent deep federated learning model for enhancing security in internet of things enabled edge computing environment
by: Nasser Nammas Albogami
Published: (2025-02-01) -
CYBER SECURITY ANALYSIS OF IOT DEVICES TRANSMITTING DATA IN THE THINGSPEAK PLATFORM CLOUD
by: DRAGOS-ALEXANDRU ANDRIOAIA
Published: (2022-10-01) -
Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities
by: Mahmoud Ragab, et al.
Published: (2025-02-01) -
Internet of Things (IoT) technologies: features, development prospects and potential threats
by: Daria Margaza, et al.
Published: (2024-11-01)