A Novel Split Learning-Based Consumer Electronics Network Traffic Anomaly Detection Framework for Smart City Environment-Reference-Cited by-同舟云学术

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A Novel Split Learning-Based Consumer Electronics Network Traffic Anomaly Detection Framework for Smart City Environment

Published:2024-02 Issue:1 Volume:70 Page:4197-4204
ISSN:0098-3063
Container-title:IEEE Transactions on Consumer Electronics
language:
Short-container-title:IEEE Trans. Consumer Electron.

Author:

Kim Dong-Jo¹^ORCID,Amma N. G. Bhuvaneswari²^ORCID,Sarveshwaran Velliangiri³^ORCID

Affiliation:

1. Department of Image design, Sunchon National University, Sunchon, South Korea

2. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

3. Department of Computational Intelligence, SRM Institute of Science and Technology, Chennai, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/30/10510045/10440147.pdf?arnumber=10440147

Reference34 articles.

1. Security in Internet of Things: A Review

2. State-of-the-Art and Research Opportunities for Next-Generation Consumer Electronics

3. IHSF: An Intelligent Solution for Improved Performance of Reliable and Time-Sensitive Flows in Hybrid SDN-Based FC IoT Systems

4. A Comprehensive Review on Artificial Intelligence/Machine Learning Algorithms for Empowering the Future IoT Toward 6G Era

5. Defense Mechanisms against DDoS Attacks in SDN Environment

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