Edge Device Identification Based on Federated Learning and Network Traffic Feature Engineering-Reference-Cited by-同舟云学术

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Edge Device Identification Based on Federated Learning and Network Traffic Feature Engineering

Published:2021 Issue: Volume: Page:1-1
ISSN:2332-7731
Container-title:IEEE Transactions on Cognitive Communications and Networking
language:
Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

He Zhimin,Yin Jie,Wang Yu,Gui Guan,Adebisi Bamidele,Ohtsuki Tomoaki,Gacanin Haris,Sari Hikmet

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/6687307/7294639/09502154.pdf?arnumber=9502154

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improved temporal IoT device identification using robust statistical features;PeerJ Computer Science;2024-07-09

2. BitIoT: A Bit Level Deep Packet Inspection Method for Identification of MQTT-Based IoT Devices in the Wild;IEEE Transactions on Network and Service Management;2024-06

3. Mean-Field Stackelberg Game-Based Security Defense and Resource Optimization in Edge Computing;Applied Sciences;2024-04-23

4. Deep federated learning hybrid optimization model based on encrypted aligned data;Pattern Recognition;2024-04

5. Network traffic classification based on federated semi-supervised learning;Journal of Systems Architecture;2024-04

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