Improving ZigBee Device Network Authentication Using Ensemble Decision Tree Classifiers With Radio Frequency Distinct Native Attribute Fingerprinting-Reference-Cited by-同舟云学术

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Improving ZigBee Device Network Authentication Using Ensemble Decision Tree Classifiers With Radio Frequency Distinct Native Attribute Fingerprinting

Published:2015-03 Issue:1 Volume:64 Page:221-233
ISSN:0018-9529
Container-title:IEEE Transactions on Reliability
language:
Short-container-title:IEEE Trans. Rel.

Author:

Patel Hiren J.,Temple Michael A.,Baldwin Rusty O.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/24/7051309/06981992.pdf?arnumber=6981992

Cited by 86 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. Pioneering advanced security solutions for reinforcement learning-based adaptive key rotation in Zigbee networks;Scientific Reports;2024-06-17

2. Cross-domain, Scalable, and Interpretable RF Device Fingerprinting;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20

3. Guessing on Dominant Paths: Understanding the Limitation of Wireless Authentication Using Channel State Information;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19

4. A Combined Filtering Method for ZigBee Indoor Distance Measurement;Sensors;2024-05-16

5. A machine learning based framework for IoT devices identification using web traffic;PEERJ COMPUT SCI;2024

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