Using Poisson Distribution to Enhance CNN-based NB-IoT LDoS Attack Detection-Reference-Cited by-同舟云学术

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Using Poisson Distribution to Enhance CNN-based NB-IoT LDoS Attack Detection

Published:2022-06-22 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Conference on Dependable and Secure Computing (DSC)
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Author:

Zeng Jiang-Yi¹,Chang Li-En¹,Cho Hsin-Hung¹,Chen Chi-Yuan¹,Chao Han-Chieh²,Yeh Kuo-Hui³

Affiliation:

1. National Ilan University,Department of Computer Science and Information Engineering,Yilan,Taiwan

2. National Dong Hwa University,Department of Engineering,Hualien,Taiwan

3. National Dong Hwa University,Department of Information Management,Hualien,Taiwan

Funder

Ministry of Science and Technology of Taiwan, R.O.C.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9888143/9888794/09888864.pdf?arnumber=9888864

Reference24 articles.

1. 5G NB-IoT: Efficient Network Traffic Filtering for Multitenant IoT Cellular Networks

2. Generator of Slow Denial-of-Service Cyber Attacks

3. Very deep convolutional networks for large-scale image recognition;simonyan;ArXiv,2014

4. Deep Residual Learning for Image Recognition

5. A digital evidence fusion method in network forensics systems with Dempster-shafer theory

Cited by 2 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. A Critical Cybersecurity Analysis and Future Research Directions for the Internet of Things: A Comprehensive Review;Sensors;2023-04-19

2. LDoS Attacks Detection for ICPS NB-IoTs Environment via SE-Based CNN;IEEE Systems Journal;2023

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