Toward Efficient Neural Networks Through Predictor-Assisted NSGA-III for Anomaly Traffic Detection of IoT-Reference-Cited by-同舟云学术

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Toward Efficient Neural Networks Through Predictor-Assisted NSGA-III for Anomaly Traffic Detection of IoT

Published:2024-06 Issue:3 Volume:10 Page:982-995
ISSN:2332-7731
Container-title:IEEE Transactions on Cognitive Communications and Networking
language:
Short-container-title:IEEE Trans. Cogn. Commun. Netw.

Author:

Wang Xinlei¹^ORCID,He Mingshu²^ORCID,Wang Jiaxuan¹,Wang Xiaojuan¹^ORCID

Affiliation:

1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China

2. School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6687307/10551670/10403928.pdf?arnumber=10403928

Reference56 articles.

1. 2020 unit 42 IoT threat report,2020

2. MobileNets: Efficient convolutional neural networks for mobile vision applications;Howard;arXiv:1704.04861,2017

3. EfficientDet: Scalable and efficient object detection;Tan;arXiv:1911.09070,2019

4. SMASH: One-shot model architecture search through hypernetworks;Brock

5. Binarizing MobileNet via evolution-based searching;Hai;arXiv:2005.06305,2020

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